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Good morning, evening and afternoon everyone, this is Josh Reed from
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the digital events team here at Genesys. And let me
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be the first to say welcome to our live demonstration
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today, ” Connect the Dots with Genesys and Adobe.” As I
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always do, I’m going to keep it short and sweet,
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but I do have just a couple housekeeping items to go
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through before we get started today. So first off, if you
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experience any problems viewing or listening to today’s demo, do
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me a favor and just do a quick refresh on
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your browser and maybe switch over to something like Chrome
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or Firefox as well, as these are the best browsers
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that support the webcast platform. You also have the ability
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to enlarge the slide window and the video window by
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dragging any of the corners of said windows, and you
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can adjust those throughout the presentation. And also note that
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this webcast is designed to be an interactive experience between
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you and our presenters today. So first off, if you
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have any questions throughout the presentation, throw those into the
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Q& A window below the slide window. Now, we will
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have a live Q& A at the end of the
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presentation today but sometimes time gets away from us. So,
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if that does happen, what we’ll do is we’ll follow
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up with you via email in a few business days.
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And also note that this is being recorded, so if
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you miss anything throughout today’s presentation, don’t fret. You’ll receive
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a link to the recording from ON24 within the next
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few business days, and that will have full playback capabilities.
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I also encourage you to check out the resource box
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below the slides as well. Clicking through won’t take you
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away, they’ll just open up in a new tab in
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your browser. But these resources expand on today’s topic. And
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lastly, we welcome and appreciate your feedback, so you’ll have
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the opportunity to fill out a short survey that’s going
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to show up at the end of today’s presentation. You
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can also click on the last icon below in that
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survey widget if you want to knock it out early,
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but we tailor these presentations to exactly what you want
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to learn more about, so I encourage you to go
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ahead and check that out whenever you get a chance
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throughout today’s presentation. And like I said, short and sweet.
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So, today we have three excellent presenters excited to discuss
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how to manage the rise of digital first customer expectations,
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eliminate data silos by integrating Genesys Cloud CX and Adobe Experience
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platforms, turn data into actionable insights that deliver results and
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enable more intelligent, individualized customer interactions. I’m happy to introduce
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you all to Alan Webber, the program vice president of
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customer experience at IDC. We have Sridhar Jayakumar, the principal
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product manager at Adobe. And finally, we have Dan Arra,
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the vice president of sales for Genesys AI. So with
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that being said, I’m going to hand things off to
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our first presenter today. Alan, the floor is yours. Thank
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you so much, and thank you everybody for joining us. Man, 2020, what a
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year. Wasn’t quite what we were expecting going into it,
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but now that we’re through it and we’re on to
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the next one, 2021, let’s talk a little bit about what it
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means to be a post- COVID customer and how companies
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are driving empathy at scale. But to start with, I’d
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like to start with a little survey, if you don’t
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mind. And if you can go ahead and answer these
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question, the question we have up in the window. What
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are the biggest changes you’ve seen over the past year
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that are driving digital transformation? And please select all that
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apply. One, need to reassure customers they can reach you
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whenever needed. Two, increase interaction volume, more calls, chats, SMS,
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messages. Three, higher customer expectations to show me that me.
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Four, demographic change mix over different channels. And five, all
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of the above. Go ahead and give you just a
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second to go ahead and answer that question for us,
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if you would please. Okay, let’s see what the results
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are showing. So, the number one, as we probably would
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have expected, at 43 1/2% was all of the above.
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The second largest was increased interaction volume. More calls, more
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chats, SMS, and messages. Third was demographic change mix over
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channels. And fourth was need to reassure customers they can
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reach you whenever needed. And lastly was the higher customer
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expectation. And that actually leads real well into what my
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presentation is about and where things are going. with the
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pandemic there were a number of effects that changed, a
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number of things that affected the consumer and the customer.
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It created unique situations for some industries, such as retail,
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healthcare, and look at hospitality. And before we got on
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the call we were talking a little bit about travel.
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The airlines have really had to change what’s going on. It has
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forced them to rethink the way they use technology to
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engage with their customers. And what I want to highlight
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is some of the effects that we’re seeing from COVID
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that are happening already. There are three cracks in what
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we call customer experience, specifically COVID cracks. And what we
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mean by that is that, with COVID we saw an acceleration
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in the digital transformation forced upon companies. They had to
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digitally transform because they weren’t ready for all of the
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impacts that the pandemic would have on them. And so,
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the three cracks, what we call, essentially exposing the digital
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underbelly are contactless experiences, customer automation and self- service, and
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apps become the interface. And we’re going to start off
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with the contactless experience. Basically what happened is, because of
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COVID we went from an in- person, person- to- person
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type of engagement and interaction to these contactless experiences. And
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it’s everything from contactless product delivery, to payment, to product
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pickup. All kinds of different things, and the whole reason
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behind that was because it made consumers and customers feel
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safer. Now, in my experience, one of the more interesting
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ones to watch was Best Buy. Before, you used to
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go into the showroom, you’d look around, there’d be stuff
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in there, lots of people in there looking at everything
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from refrigerators, to new iPhones, to new computers. In the
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pandemic, actually Best Buy was well- positioned to deal with
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this transformation, and just a few months in they’d already
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switched over to the ability to do curbside pickup, order
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online, look into their supply chain. What we found is
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that, with customers, 38% of them said during our surveys
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that contactless experiences make them feel a lot safer, or
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much safer. What kind of contactless experiences? Specifically, contactless product
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delivery. That was the most preferred contactless approach. So everything
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from DoorDash to something coming from Amazon. But right up
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there was contactless payment, product pick up, check- in, customer
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service, and no- signature checkout. But that was just the
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start. That was just the first crack that we saw.
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But how does this actually manifest in the world it
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is that we’re dealing with today? And probably the best
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example we have out there is actually grocery pick up.
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30. 5, almost 31% of consumers said they would like
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curbside pick up to continue. Not really unexpected because by
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2023, IDC expects 75% of grocery e- commerce orders will be
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picked up curbside or in- store at a special type
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of kiosk, driving a 35% increase in investment in on-
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site or nearby micro- fulfillment centers to meet that need
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of the customer. We talked a little bit about contactless
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experience, what’s the next one? Well, that’s customer automation and
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self- service. That’s one of the things that grew fairly
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quickly during the whole pandemic, is customer automation and self-
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service. How do customers take care of things themselves? How
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do they actually, instead of going into a store or
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going into a location somewhere, how are they able to
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do it digitally, online, and move that forward? And so,
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what we found is that, during COVID- 19 and the
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pandemic, there were a lot of increases in adoption around
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the usage and adoption of automated self- service technologies. So
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for example, the use of telemedicine, first- time use of
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telemedicine, was up 28. 2%. Video calls, Zoom calls, Teams
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calls, WebEx calls went up 26.2%. Mobile ordering went up
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20. 5%, people actually ordering things on their phone. Everything
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from Amazon to, say Chipotle or Chic- Fil-A. But that
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wasn’t just it. What’s also increased is that push towards
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mobile apps and how we do automated and self- service
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through mobile apps. In fact, mobile applications, their usage of
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by consumers and customers went up almost 36%. Mobile ordering
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was up 27. 5% previously. Mobile payments, and this is
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one of the really interesting ones, between that and alternative payments, mobile
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payments was up 18%. Alternative payments, using things like PayPal,
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Venmo, things like that, was up almost 23%. So first
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of all, we saw the digital transformation around contactless experiences.
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And then we see this move into customer support and
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self- service, all being automated and again, in a lot
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of ways, contactless. So how has this manifested out into
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the world? Well specifically when you talk about telemedicine, this
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is probably one of the biggest changes because with healthcare,
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a lot of that is that personal interaction back and
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forth with the doctor or other healthcare provider, and IDC
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believes that telemedicine is here to stay just because it’s
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a simpler and easier way to interact and engage with
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your healthcare providers. For example, one of my children goes
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and sees a speech therapist and it used to be
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this was all done in person. Now what happens is
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that he has a weekly appointment with his speech therapist
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through Zoom and they’re able to interact and engage, and the
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audio and the video is good enough that they can
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actually make those necessary changes and teach him what it
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is he needs to adapt to his speech therapy. So,
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telemedicine is one of those things that are here to
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stay, and IDC believes by 2023, providers and life science companies
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will increase spending by 70% on health technologies, specifically those
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health telemedicine type technologies. So we continue to move that
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forward. Now we’ve talked about contactless experiences, we’ve talked about
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the consumer automation. Lastly, it’s really the applications become the
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primary interface for how we interact and engage with the
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world. With COVID- 19, it introduced a whole lot of new
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task apps that we’ve never had on our phones before.
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We’re used to having things like email, we’re used to
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having maybe FaceTime. Maybe you’re checking Facebook or doing doomscrolling
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on TikTok or maybe Instagram. But the fact of the
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matter is that we have a lot of new apps
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that were task- oriented that were introduced during COVID- 19.
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Probably the biggest one introduced, obviously, was the COVID incident
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management applications and symptom tracking. But the fascinating thing is,
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as we get through the pandemic, those are going to
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drop away but what’s going to stay in place? The
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workplace safety applications, the curbside pickup applications, and the office
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space utilization applications. You’re going to see a whole lot
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more new applications that lay out how it is we
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interact and engage, both with other employees and with customers
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and consumers as they’re out there. So this is the
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new world that we’re dealing with. A lot of this
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is going to be happening through those mobile devices. In
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fact, probably one of the best examples that I can give
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during this whole process was the whole food delivery. One
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of the fabulous things about being home now, when I
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used to travel so much, is that I had a
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number of dollars stashed up in Uber Cash. And so,
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it was fun when my kids were home from school
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that they would come in and they would say, ” Okay,
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he Dad, can we order Uber Eats using the money
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you have on your Uber app?” And that was kind
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of cool for a couple of times. After the third
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time, it’s like, ” No, you can go downstairs and make
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yourself a PB& J. But the fact of the matter
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is that food delivery is not going away. It’s something
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to stay. And it’s going to increase for restaurants and
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eats into their profits just as a way to be
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able to survive. 31% of consumers would like home delivery
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of goods to continue. And honestly, I think this is
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going to grow. I don’t know how many of you
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remember the old Peapod and places like that where they
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would actually deliver groceries. This is going to grow even
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more. In fact, IDC believes by 2023, 30% of restaurants
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using third party delivery platforms will deploy native delivery options
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to eliminate that third party feed because they want to
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retain that money. What that means is that they’re using
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technology to continue to build up their baseline revenue in
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this new type of world it is that we’re dealing
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with. So, if you work in technology, if you’re CIO,
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a CTO, a CMO, what does this mean for you? Well, here’s
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what it means for you. CX is now becoming urgent
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for the C- Suite. IDC does a lot of research,
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we take a lot of surveys, and back in January
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or February we surveyed what we call our future enterprise
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survey. And we had CxO type officers outline where the
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primary priorities were for the C- Suite in their companies.
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And customer experience was down number eight because there’s so
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many other things that are going on out there. And
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most companies honestly believe that they can always find another
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customer. What we found is that with the pandemic, customer
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experience went from number eight to number two, and it
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remained in one of the top three slots every month
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for the rest of the year. This is where the
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priority was. Customer experience become a top priority because companies
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realize that without a customer, they didn’t have a company.
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So what are the challenges to driving a differentiated experience?
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Again, from our survey, the biggest challenge out there is
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that cross- channel experience. How do you move from a
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mobile device to a website to an in- person, and
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maybe back to a mobile device? 69% of our respondents
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said that was the number- one thing they were challenged
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with. The number two was how do you switch, in
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a pandemic environment, into a customer- centric organization? What does
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it take and how do you move that forward? Third
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was tying that improvement in customer experience to revenue, and
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that’s absolutely critical because if you can’t prove the revenue,
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then you can’t prove the value of the experience. And
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the last one, all the way down at 38% was
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integrated the customer data. Now I’ll just tell you from
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experience, you’re going to see this one rise because this
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is the lifeblood of customer experience. If you look at
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the work that Genesys and Adobe do, this is really
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the lifeblood. The customer data, moving that customer data around
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and being able to drive all of the intelligence and
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analytics, and therefore the better experience that they’re able to
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provide. So, when you think about where this goes in
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the future, think about starting with the customer at the
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center. This is where the future is going to be
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and this is how companies like Adobe and Genesys are
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pulling this together. Customers at the center, and they want
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four things. They want a conversation with the brand, they
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want a clear customer journey, they want a good experience,
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and they want satisfaction and being able to express that
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satisfaction. So really, what it comes down to is an
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empathetic relationship between customers and brands built upon what the
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customer wants and how they want to be treated. But
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that’s just the beginning because this all happens through this
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lens of technology. And it’s this technology around awareness, engaging,
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learning and measuring. Every customer engagement now happens through a
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lens of technology, and that’s the critical piece here. Lastly,
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you’ve got the customer, you’ve got the technology. It has
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to drive business outcomes that drives empathy at scale. That’s
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really where the future is now, is empathy at scale.
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And that’s what technology is driving, and that’s what that
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relationship with the customer is all about. So this is what
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I’d like to leave you with because this is what
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it means. The customer experience of today and tomorrow is
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all about awareness. It’s about engagement. It’s about learning. It’s
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about measurement. And it’s about data. And these, together, are
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what drive empathy at scale, and all this happens through
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the lens of technology. Now I’d like to turn it
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over to my colleagues and let them take this forward
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from here. Great. Thank you very much, Alan. A lot
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of good information. We’d like to learn a little bit
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more about your specific CX challenges before Sridhar and I
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start talking about the Adobe Genesys partnership and integrations. So
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we have a question here and a few options. What
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are your CX challenges in the new digital world? One,
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improve customer retention/ loyalty, reduce churn. That’s probably pretty important.
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Personalize the experiences to impact very specific KPIs. CSAT, increase
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revenue, increase lead velocity, and for those contact center people
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out there, first call resolution, average handle time. Are those
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important KPIs? Are you focused on reducing the call interaction
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volume through automation, using bots or chats rather than calls?
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And do you have commitments to your customers, whether they’re
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internal within your organization or to external customers, to meet
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service level agreements? So, let’s take a look at the
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results. So, reducing call interaction volume. That’s pretty interesting, that’s
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very good. So, as Alan was describing, the increase of
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volume of interactions going up, being able to handle those
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using AI. And second, these KPI metrics or specific revenue
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and lead velocity metrics, they’re pretty important as well. And
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reducing churn, increasing loyalty. And then finally, meeting your service
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level agreements. Great. All right, so as I mentioned, we’re
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here to talk about a new strategic partnership between Genesys
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and Adobe, a very exciting partnership. We’ll describe what that
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partnership is, talk about the integrations between our two platforms,
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and then we’re going to give you a demonstration that actually shows you
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how we break down these silos between marketing, commerce, sales
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and service across the entire customer life cycle, customer journey,
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to utilize the data that exists, the behaviors that occur,
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so we can link the marketing profiles with contact history
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for real- time engagement. And the goal is to allow
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you to see and know more about your customers, personalize
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better, and engage smarter and faster to achieve some of
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those KPIs that we were just talking about. And another
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way to look at this is we’re leveraging each other’s
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strengths, Adobe and Genesys. Genesys is a contact center platform,
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customer experience platform, focused on real- time engagement. Most of
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the engagement is one- to- one between an agent or
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an employee and a customer, and a marketing or digital
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experience platform from Adobe, they’re focused on communicating one- to-
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many, as marketeers do. And we want to leverage the
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data that exists in the contact center and all of
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the other connection points that we have in the contact
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center, with the data and marketing technology stack that exists
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in the sales and marketing part of the organization to
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develop this single unified view so we have better conversations,
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as Alan was describing, clearer journeys, and good experiences for
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the customer in context. So we’re engaging at the right
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moments with the right information to make the employees smarter,
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the customers happier, and the outcomes better so that those
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customers are satisfied. So Alan was describing the trends that
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he’s seen in the COVID world. Let’s hear a little
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bit from Sridhar about the trends that Adobe is seeing.
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Sridhar? Thank you, Dan. And like Alan was pointing out,
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in this COVID and post- COVID era, with cashless payments
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or contactless experiences, one of the key motivators for customers and businesses,
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we find ourselves to be in a very fortunate position
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to be the nexus of many of these micro trends.
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I’m not going to go through all of them but I’ll
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just pick a few of them which actually might resonate
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with you. The first one is, this is actually the
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golden age of design and creativity. So design is actually
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competitive advantage for businesses, large and small. How they present
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themselves, how they make things easier for customers to interact
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with, as well as how they use technology as a
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canvas for exploring new areas, whether it is voice, or
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VR, AR, or artificial intelligence, things like that. The second
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one is, technology is actually reshaping productivity. So documents continue
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to still be the core of how people work, so if we look
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at realtors, if we look at any major business, they are moving
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non- paper artifact whether it is using Adobe Sign or
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any other mechanism of creating via the web or email
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without having to actually having to pick up a paper and
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sign the paper. The third one is around how experiences
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matter more now than ever. The first one is customers will
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need to know and anticipate what their customers will want
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from them, and why they are contacting them in the first place.
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And second one is the data itself. The more data
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which they collect today becomes a mandate of how they’re
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going to protect the data, as well as being transparent
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about how they are going to use this data. And
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all these trends are all by artificial intelligence and machine
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learning. They accelerate these trends. Speaking about Adobe, what Adobe
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does, Adobe was founded in 1982 and since then, from
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the beginning, setting the standard for digital experiences has been
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one of the prime goals or motivation factors for us. At Adobe,
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our mission is to change the world through digital experiences. So,
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from the moment you wake up in the morning until
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you go to bed at night are the media you
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consume, the content that you see on your mobile phone,
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or the websites you browse through, or the apps that you use, at some
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point they all actually have some sort of connectivity or
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touched by Adobe technology, whether it is the creations that you
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see done via Photoshop or Illustrator, or whether it is
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the pages that are delivered via the Experience Manager or
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the personal Adobe Target, there is always some sort of
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Adobe’s presence in the gadgets that you use, as well
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as the content that we consume today. At its essence, Adobe
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gives everyone, from emerging artists to global grants, everything they
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need to design and deliver exceptional digital experiences. I would
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like to walk through how we see current technology landscape
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in this specific era. So, coming to strategy, right? So,
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originally Adobe was known as a company that deals with
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creating creative tools that will help creators, designers, whether it
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is creating a nice image in Photoshop or to create
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banners or content within Acrobat, or InDesign, or Dreamweaver. Over the
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last decade or so, we have been slowly merging both the creative
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business as well as the marketing business, so all the
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creative artifacts that are developed by these creator people will
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need to get into the consumer’s hands. Whether it is
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via web or whether it is via print media. So
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we do all that, so within the marketing business, we
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have our Experience Manager for edge delivery, we have analytics
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to get insights of what is currently being viewed, what
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customers like, what they don’t like, where they currently need.
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And then we also provide targeting campaigns and other via
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marketing cloud products. And then, like I said earlier, the
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move from paper to print, or paper to digital, that
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transformation has also been happening for quite some time now.
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We have Adobe Sign as well as we also have Acrobat,
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which in that aspect. Great, so we’ve heard a bit
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about Adobe strategy. Oops, let me back up here. Adobe
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strategy, and I’ll highlight how Adobe strategy and the Genesys
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strategy are very complementary. We’ve been around a long time
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as well, 30 years, and we have many of the
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same customers. We are listing some very recognizable brands here
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and large companies, but I want to emphasize that we
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also have customers in the small, medium, large business category,
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not just enterprise customers. And many of these customers are
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very large, and they have many, many agents interacting with,
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and customers, which results in a great deal of data
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that is derived from the massive amount of interactions that
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are occurring on a daily basis. So, we are utilizing
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that data to become smarter and to optimize the customer
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experience. And leveraging the customer service tech stack, the agents,
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and users of the platform on the left side of
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the wall. And we’re also leveraging now with the partnership
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by breaking down that wall to leverage the data and
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the insights that exist from the Adobe platform. So we’ll
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know things like which campaigns appealed to a customer who
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might be calling in for support. And we can leverage
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that to eliminate a disjointed customer experience. Many times we
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think of receiving emails and information from businesses via one
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channel and one experience, but as a consumer, we shop,
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we buy, and we get customer care and we do
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that with the business. And we want to make sure
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that, as consumers, we have this very tightly integrated experience.
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And, as you highlighted in the survey question, one of
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your challenges to eliminate these disjointed experiences. And you also
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want to deliver what the customer needs. Products that they
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need, services that they need, to increase the value that
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you’re receiving and delivering to those customers. And again, leveraging
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the data and the technology on both sides of that
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wall, we can fulfill the brand promise that’s often made
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by the marketing side of the house but the customer
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care and the people that are engaging in real- time
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are often the people who have to deliver on that
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brand promise, to show the customer that we know them,
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to demonstrate that we value the information that they’ve shared.
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And we’ve been paying attention to these interactions so that
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we can know the best ways, the best moments, to
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engage. And this is really the essence of what we
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call experience as a service. There are many companies that
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we interact with, we categorize them here as the companies
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you swear at, right? Where you’ve been invited to their
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business and you call them and the first thing they
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do is ask you questions as if they don’t know
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who you are. Who are you, and why are you calling? It’s like inviting
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somebody over to your house for dinner, and you open
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the door and you say, ” Who are you and why
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are you here?” So, being able to understand the invitations,
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the marketing campaigns, that are driving people to your business,
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either to your website or to your call center over
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the phone, we want to make sure that we are
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aware of the entire customer life cycle so that we
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can deliver these empathetic experiences, what we call experiences as
461
00:30:18,810 –> 00:30:25,610
a service. The essence of empathy is paying attention. Observing,
462
00:30:25,710 –> 00:30:31,730
listening and understanding, and then remembering in context. When somebody
463
00:30:31,840 –> 00:30:36,330
is engaging with your business, they don’t necessarily follow a
464
00:30:36,380 –> 00:30:42,860
linear path from shopping, buying, et cetera. There is a
465
00:30:42,860 –> 00:30:46,770
lot of contextual changes. You may make a purchase and
466
00:30:46,770 –> 00:30:50,830
then you may have a support question. Or you may
467
00:30:50,830 –> 00:30:54,830
want to return a product. So being aware of what
468
00:30:54,830 –> 00:30:58,580
has happened across the entire customer life cycle is going
469
00:30:58,580 –> 00:31:02,780
to help you respond efficiently and in a way that
470
00:31:02,780 –> 00:31:06,500
shows the customer that you really value the information that
471
00:31:06,550 –> 00:31:10,160
they have shared with you. So Sridhar, maybe you could
472
00:31:10,160 –> 00:31:12,990
talk a little bit about the underlying technology and how
473
00:31:12,990 –> 00:31:18,260
we deliver this together. Sure, thank you. So, for the
474
00:31:18,260 –> 00:31:21,850
experience as a business, what we currently want to push here
475
00:31:22,110 –> 00:31:25,250
with this particular Genesys partnership is our Adobe Experience Cloud
476
00:31:25,250 –> 00:31:28,760
Solution that we are working to pair with Genesys. Adobe Experience
477
00:31:28,760 –> 00:31:33,570
Cloud is the industry’s most comprehensive solution for marketing, advertising,
478
00:31:33,630 –> 00:31:38,290
analytics and commerce, serving both B to C or B
479
00:31:38,290 –> 00:31:43,070
to B customers. Experience Cloud allows you to deliver exceptional experiences
480
00:31:43,070 –> 00:31:47,660
from creation all the way through to monetization, acquisition, retention,
481
00:31:47,660 –> 00:31:52,330
and even renewal of existing services that the brands might
482
00:31:52,330 –> 00:31:55,130
want to give to their customers. And at the core
483
00:31:55,340 –> 00:31:58,430
of the Experience Cloud, we have the Experience platform, which
484
00:31:58,830 –> 00:32:03,530
is our new strategic initiative for integrating with the different
485
00:32:03,580 –> 00:32:08,270
clouds versus different services, wherein we are able to pull in
486
00:32:08,270 –> 00:32:11,690
data from different parties, whether it is a customer’s online
487
00:32:11,690 –> 00:32:16,710
behavior via Adobe Analytics, or information that we collect via
488
00:32:16,710 –> 00:32:21,650
different DSPs or data providers and as well as campaigns
489
00:32:21,650 –> 00:32:25,160
that sends out emails to customers, and how a customer
490
00:32:25,170 –> 00:32:29,480
reacts to a particular targeted or personalized messages. All this
491
00:32:29,480 –> 00:32:32,380
data is now in the platform, and we use machine
492
00:32:32,380 –> 00:32:37,370
learning and artificial intelligence to uncover new insights and information
493
00:32:37,370 –> 00:32:43,590
that was not previously available. At the center of this
494
00:32:43,590 –> 00:32:48,210
platform, we have something called the real-time customer profile. So,
495
00:32:48,230 –> 00:32:51,330
when I go to a particular retail store, the store
496
00:32:51,330 –> 00:32:54,820
would know me as in and buying a particular device,
497
00:32:55,100 –> 00:32:59,950
or buying a particular product. As well as when I
498
00:32:59,950 –> 00:33:04,410
go online and search for similar for what I just
499
00:33:04,410 –> 00:33:07,670
bought, or even look up support information or any sort
500
00:33:07,670 –> 00:33:10,060
of issues that I want to get resolved, I’ll be
501
00:33:10,060 –> 00:33:11,950
using my email address to sign in, or I may
502
00:33:11,950 –> 00:33:14,710
be using my Facebook or my social media handles to
503
00:33:14,710 –> 00:33:18,270
connect. And this profile information is very disparate, right? So
504
00:33:18,270 –> 00:33:21,210
the way I interact with the particular brand could happen
505
00:33:21,210 –> 00:33:24,130
differently. And again, this could be happening from a mobile
506
00:33:24,130 –> 00:33:27,120
device, or from a laptop, or even in- person or
507
00:33:27,120 –> 00:33:31,730
offline, which is happening. And when we put all these
508
00:33:31,730 –> 00:33:36,010
data into one particular environment, it becomes very hard for
509
00:33:36,560 –> 00:33:38,900
analysts as well as marketers to figure out what is
510
00:33:38,900 –> 00:33:42,260
exactly happening. Why is a particular sale happening in the
511
00:33:42,260 –> 00:33:45,420
way it is happening? Or why exactly a consumer is
512
00:33:45,420 –> 00:33:47,980
not too happy with the brand? So what we are
513
00:33:47,980 –> 00:33:49,760
doing here is we are bringing in all the data
514
00:33:49,760 –> 00:33:54,330
into the platform, along with things like the customer’s interaction
515
00:33:54,350 –> 00:33:58,480
at the store level, the service that is complete online, as
516
00:33:58,480 –> 00:34:00,650
well as the point of sale, as well as a
517
00:34:00,650 –> 00:34:04,280
Genesys- provided customer experience data. That could be call center
518
00:34:04,280 –> 00:34:07,660
data, could be anything that Genesys gives to the platform. And
519
00:34:07,660 –> 00:34:10,880
all this data is stitched together, and it is available at
520
00:34:10,880 –> 00:34:14,730
the edge, meaning it is available for marketers, it’s available
521
00:34:14,730 –> 00:34:17,940
for call center agents, could be available for service people,
522
00:34:18,280 –> 00:34:21,130
at the edge instantaneously. Again, we are talking about less
523
00:34:21,130 –> 00:34:25,400
than a few milliseconds here. And this enables them to
524
00:34:25,400 –> 00:34:28,590
quickly interact with the person with the latest knowledge about
525
00:34:28,650 –> 00:34:31,180
what they have gone through, or what is the right
526
00:34:31,180 –> 00:34:35,560
level of interaction that they would want to come back. Empathy as
527
00:34:35,560 –> 00:34:44,830
a service. Let’s take a look at how this interaction
528
00:34:44,920 –> 00:34:50,630
would work. What would the experience feel like? So, we’re showing
529
00:34:50,630 –> 00:34:56,710
here a customer arriving on a website or calling into
530
00:34:56,710 –> 00:35:02,480
the contact center. And when they do that, the integrations
531
00:35:02,480 –> 00:35:06,650
we have between our platform, the Genesys platform, and the Adobe platform,
532
00:35:07,020 –> 00:35:11,140
we’re able to pull data out of the Experience Cloud
533
00:35:11,140 –> 00:35:17,650
platform, or the Adobe Experience platform, or Adobe Analytics, grab
534
00:35:17,650 –> 00:35:21,850
that information into the agent desktop in a consumable way
535
00:35:22,420 –> 00:35:26,460
to make the agent more knowledgeable about what brought the
536
00:35:26,460 –> 00:35:28,990
customer here, why are they calling us today? Why are
537
00:35:28,990 –> 00:35:33,270
they engaging? What were they doing before, during and after
538
00:35:33,270 –> 00:35:37,330
the interaction? And we can even pull product recommendations out
539
00:35:37,330 –> 00:35:41,740
so we have more relevant, contextual suggestions for the customer
540
00:35:42,000 –> 00:35:45,660
about products or services they may want to buy. And
541
00:35:45,660 –> 00:35:51,040
we can push and pull data during that interaction, and
542
00:35:51,040 –> 00:35:54,130
at the end of that interaction, to enrich the customer
543
00:35:54,130 –> 00:35:59,810
profile, to inform subsequent marketing campaigns about what the customer
544
00:35:59,810 –> 00:36:03,580
shared in that live conversation with an agent or support
545
00:36:03,580 –> 00:36:08,540
person so that at what stage that customer is in
546
00:36:08,540 –> 00:36:12,260
their buying decision. And that will inform what information to
547
00:36:12,260 –> 00:36:15,910
deliver to them to move them more efficiently, and in
548
00:36:16,040 –> 00:36:19,550
a better way, through the sales cycle, through the funnel.
549
00:36:20,240 –> 00:36:23,800
And we can also use these insights to trigger engagement
550
00:36:24,040 –> 00:36:28,040
more intelligently so you’re engaging at the right moments with
551
00:36:28,040 –> 00:36:32,420
the right information to drive the best outcome. So this
552
00:36:32,940 –> 00:36:37,590
real- time exchange of data really helps to optimize the
553
00:36:37,590 –> 00:36:45,310
experience and give you this integrated picture of who that
554
00:36:45,310 –> 00:36:50,210
customer is. So, we’re showing examples of customer experience data
555
00:36:50,210 –> 00:36:54,380
from the contact center, customer experience data from the various
556
00:36:55,140 –> 00:36:58,880
Adobe products that have been consolidated into the Adobe Experience
557
00:36:58,880 –> 00:37:04,560
platform to simplify and streamline the access to that data
558
00:37:04,830 –> 00:37:09,820
so that we can update the information in the moment
559
00:37:10,040 –> 00:37:15,980
and then use that during the conversation to impressionalize and
560
00:37:15,980 –> 00:37:20,120
optimize the experience for the customer. So, let me show
561
00:37:20,120 –> 00:37:27,020
you how this works by sharing my desktop. And I’m
562
00:37:27,170 –> 00:37:32,680
going to show you the solution, and I’m going to
563
00:37:32,800 –> 00:37:38,860
describe what the experience would look like with a customer
564
00:37:38,860 –> 00:37:43,980
either arriving on a website or dialing into the contact
565
00:37:43,980 –> 00:37:47,670
center. So, on the left we have a website, and
566
00:37:47,670 –> 00:37:50,530
the customer may have arrived on this website from a
567
00:37:50,530 –> 00:37:53,880
marketing campaign, or they may have just picked up the
568
00:37:53,880 –> 00:37:57,050
phone and called into the contact center. So on the
569
00:37:57,050 –> 00:38:00,150
right here, we’re taking a peek under the hood of
570
00:38:00,150 –> 00:38:06,300
the Genesys platform and we’re observing unknown visitors or callers,
571
00:38:06,520 –> 00:38:12,140
known visitors based upon their cookie, email, login, or recognized
572
00:38:12,140 –> 00:38:15,920
phone number. And we’re connecting in the back end with
573
00:38:15,920 –> 00:38:19,300
the Adobe Experience platform and other Adobe products. So we’ve
574
00:38:19,300 –> 00:38:23,450
got the Genesys platform, the Adobe platform, and we’re connecting
575
00:38:23,450 –> 00:38:27,160
these dots. And here we’re going to view what the
576
00:38:27,160 –> 00:38:31,910
platform can see about this one unknown visitor. So, first
577
00:38:31,910 –> 00:38:34,820
I’m showing you the platform view. This is not the
578
00:38:34,820 –> 00:38:39,270
agent view. This is what the platform can see. And as this
579
00:38:39,270 –> 00:38:41,970
visitor on the left, who may have arrived from a
580
00:38:41,970 –> 00:38:46,120
marketing campaign, begins to navigate around on the site, you’ll
581
00:38:46,120 –> 00:38:50,850
see that we’re observing, analyzing their behavior in real- time.
582
00:38:51,140 –> 00:38:53,960
We don’t know who this visitor is, they’re unknown, but we
583
00:38:53,960 –> 00:38:58,420
have some demographic and technographic information that may inform us
584
00:38:58,630 –> 00:39:01,520
a bit more about how, when, and with whom to
585
00:39:01,520 –> 00:39:05,240
engage. And then we can see here, previous visits that
586
00:39:05,240 –> 00:39:07,500
may have occurred, even though this person is unknown. They
587
00:39:07,500 –> 00:39:12,230
may have, without sharing their identity, visited our site over
588
00:39:12,380 –> 00:39:16,940
the past several months. And if the customer, visitor, starts
589
00:39:16,940 –> 00:39:20,240
to do things like add items to their shopping cart,
590
00:39:21,460 –> 00:39:24,780
or they could be filling out an application, we’re able
591
00:39:24,780 –> 00:39:28,620
to see that they’ve added items to their cart, what
592
00:39:28,620 –> 00:39:32,620
item, the dollar amount, the product category. We can track
593
00:39:32,750 –> 00:39:36,420
whether the cart value is increasing or decreasing, and we’re
594
00:39:36,420 –> 00:39:41,570
making predictions about whether they’re likely to make a purchase
595
00:39:41,820 –> 00:39:45,340
or fill out a lead form. These outcomes make sense
596
00:39:45,340 –> 00:39:49,560
for the G- Sol business. You would configure different outcomes.
597
00:39:49,740 –> 00:39:52,150
And once those outcomes are configured, we start to look
598
00:39:52,150 –> 00:39:55,540
at the attributes and behaviors of all those who achieve
599
00:39:55,920 –> 00:39:59,240
that outcome, and that’s how we’re making these predictions. So
600
00:39:59,240 –> 00:40:01,520
if this person decides they would like to log in
601
00:40:02,080 –> 00:40:05,980
and share a bit more information about themselves, maybe they’ve
602
00:40:05,980 –> 00:40:09,340
got stored payment information here and they’d like to log
603
00:40:09,340 –> 00:40:11,990
in so they can use that before proceeding to check
604
00:40:11,990 –> 00:40:15,900
out. Now you’ll see a few things changing here. Now
605
00:40:15,900 –> 00:40:19,330
that we know who this person is, we can start
606
00:40:19,330 –> 00:40:24,330
to decide which communication options to present to the customer.
607
00:40:25,240 –> 00:40:29,950
So we’ve presented here a live assistance widget that shows
608
00:40:29,950 –> 00:40:33,240
me, on the left, that I can call or initiate
609
00:40:33,240 –> 00:40:38,240
a web chat. We’ve got some customer- initiated options. But
610
00:40:38,240 –> 00:40:41,870
if the customer proceeds here in their journey to begin
611
00:40:41,870 –> 00:40:46,310
to check out, they are wondering about this discount code.
612
00:40:46,750 –> 00:40:50,250
Maybe they search for the discount code, and they don’t
613
00:40:50,250 –> 00:40:54,220
find what they’re searching for. What is going to happen
614
00:40:54,220 –> 00:40:59,280
is we will proactively offer that visitor a very personalized
615
00:40:59,280 –> 00:41:04,510
tailored interaction. A chat interaction will appear that asks them, ”
616
00:41:04,570 –> 00:41:08,370
Would you like a chat? You have a discount that
617
00:41:08,370 –> 00:41:11,730
applies.” So again, we’re leveraging the insights here, and we’re
618
00:41:11,730 –> 00:41:14,120
not asking, ” Hey, who are you? How can we help
619
00:41:14,120 –> 00:41:17,130
you?” We’re suggesting that you may need help with your
620
00:41:17,130 –> 00:41:21,320
purchase. And when the customer accepts that interaction and starts
621
00:41:21,320 –> 00:41:25,820
to chat, we’re first engaging with a chat bot. So
622
00:41:25,820 –> 00:41:29,900
the customer may ask questions about, ” When can you ship?”
623
00:41:31,910 –> 00:41:35,630
And the chat bot may be able to answer this question. And
624
00:41:35,630 –> 00:41:38,370
he does. And then now, ” Great, now I would like
625
00:41:38,370 –> 00:41:40,410
to talk to an agent, please, because I’d like to
626
00:41:40,410 –> 00:41:47,250
make a purchase.” So when the visitor requests and agent,
627
00:41:47,490 –> 00:41:51,610
you’ll see here an inbound alert notifying me that I
628
00:41:51,610 –> 00:41:56,220
have a incoming chat. So the first thing we’ll see
629
00:41:56,220 –> 00:41:59,700
is, as an agent… Now before, I want to remind
630
00:41:59,700 –> 00:42:03,290
you we were just observing, analyzing, predicting all of the
631
00:42:03,290 –> 00:42:07,310
visitors and callers, whether they needed help based upon their
632
00:42:07,310 –> 00:42:10,090
behaviors and the data that we have from the Adobe
633
00:42:10,090 –> 00:42:13,750
platform combined with what we were seeing in the Genesys
634
00:42:13,750 –> 00:42:17,670
platform and what was happening on the website. But now,
635
00:42:17,670 –> 00:42:20,190
we’re in an interaction and the agent, at a glance,
636
00:42:20,190 –> 00:42:24,520
can see what the bot conversation was before they were
637
00:42:24,520 –> 00:42:28,010
connected to the agent. We can see what outcomes the
638
00:42:28,010 –> 00:42:31,550
customer was likely to achieve or unlikely to achieve, what
639
00:42:31,550 –> 00:42:36,270
segments they may have matched. And we can even see
640
00:42:36,290 –> 00:42:39,670
this live behavior on the website. We can scroll down
641
00:42:39,670 –> 00:42:45,180
here and see what happened, say, six days ago. They
642
00:42:45,180 –> 00:42:47,730
placed a call. Who did they talk to? What was
643
00:42:47,730 –> 00:42:51,560
their outcome disposition? Maybe they placed an order and a
644
00:42:51,560 –> 00:42:54,950
product was shipped. So we have the ability to look
645
00:42:54,950 –> 00:42:59,970
more deeply into the customer experience across days, weeks, different
646
00:42:59,970 –> 00:43:04,550
channels, and we can observe here, in the moment, what
647
00:43:04,550 –> 00:43:08,050
the customer was searching for, what they may have in
648
00:43:08,050 –> 00:43:12,030
their shopping cart, what segments they may have matched. So
649
00:43:12,030 –> 00:43:15,890
now, I’m much more effective as an agent, much smarter,
650
00:43:15,890 –> 00:43:20,050
I can ideally be on the phone or in the
651
00:43:20,050 –> 00:43:22,120
chat in a shorter period of time. I can jump
652
00:43:22,120 –> 00:43:28,190
right to the canned responses that may be relevant to
653
00:43:28,190 –> 00:43:31,180
the customer. Probably searching for a discount code. I’ve got
654
00:43:31,180 –> 00:43:34,360
a discount code right here. I can pop that into
655
00:43:34,360 –> 00:43:37,410
the chat and share that with the customer. Guiding the
656
00:43:37,410 –> 00:43:40,750
customer back to their shopping cart so they can proceed
657
00:43:40,750 –> 00:43:45,580
to check out, enter that information, and achieve this outcome.
658
00:43:47,030 –> 00:43:50,140
And all this information is being updated as you see
659
00:43:50,140 –> 00:43:54,270
it in real- time and can be propagated into the
660
00:43:54,430 –> 00:43:59,700
various Adobe products, including the Adobe Experience platform so that
661
00:43:59,700 –> 00:44:04,450
we now know if a customer purchased during a chat,
662
00:44:04,640 –> 00:44:08,680
purchased over the phone, we can share that information and
663
00:44:08,680 –> 00:44:12,080
connect those dots so we have the real- time engagement
664
00:44:12,670 –> 00:44:17,000
interactions and we know how many chats or calls it
665
00:44:17,000 –> 00:44:20,870
took to help a customer achieve an outcome. That may
666
00:44:20,870 –> 00:44:26,100
inform future marketing campaigns so that we can tailor them,
667
00:44:26,320 –> 00:44:31,100
tailor the content that is guiding the customer to the
668
00:44:31,100 –> 00:44:34,620
right place so they are not calling when they can
669
00:44:34,620 –> 00:44:38,100
self- serve. They’re not asking questions about information that may
670
00:44:38,100 –> 00:44:42,150
be available at their fingertips on the website. So it’s
671
00:44:42,150 –> 00:44:46,850
a much more efficient way to engage, and it shows
672
00:44:46,850 –> 00:44:50,870
the customer that them, right? So we’re able to take
673
00:44:50,870 –> 00:44:54,970
advantage of the data and information that’s here, pulling together
674
00:44:55,210 –> 00:45:00,470
information from the Adobe platform in real- time to make
675
00:45:00,480 –> 00:45:04,990
the agents or reps smarter, the customers happier, and guide
676
00:45:04,990 –> 00:45:10,990
the customer to a better outcome. So, let’s go back
677
00:45:11,070 –> 00:45:21,910
to our slides and let’s review here what we’ve shown
678
00:45:21,910 –> 00:45:28,540
you. So, we’ve tied together the customer experience from marketing,
679
00:45:28,650 –> 00:45:31,960
sales and care. We leveraged all of the information that
680
00:45:31,960 –> 00:45:35,800
was there, we’re much more knowledgeable about what campaigns may
681
00:45:35,800 –> 00:45:38,880
have brought the customer to the site, what things they
682
00:45:38,880 –> 00:45:42,180
were interested in, not interested in. So we could be
683
00:45:42,180 –> 00:45:45,020
much more effective at upselling and cross- selling at the
684
00:45:45,020 –> 00:45:49,240
end of that support call. We’ve all had these experiences
685
00:45:49,240 –> 00:45:52,740
where we call our cable or internet provider about a
686
00:45:52,740 –> 00:45:56,020
support issue, and at the end of the call they try
687
00:45:56,020 –> 00:45:59,100
to sell you something. The try to sell you the sports
688
00:45:59,100 –> 00:46:03,300
channel, or the movie channel, and you say to yourself, ”
689
00:46:03,910 –> 00:46:06,930
No, I’m not interested in that. Why are you asking
690
00:46:06,930 –> 00:46:10,430
me this? You should know. Aren’t you listening to me?”
691
00:46:10,830 –> 00:46:15,650
So, in this use of our integrated solutions, we’re able
692
00:46:15,650 –> 00:46:18,580
to show that we are listening to the customer and
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00:46:18,580 –> 00:46:22,100
we know what are their interests, and we can suggest
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00:46:22,270 –> 00:46:25,830
products that they’re more likely to buy, services that they’re
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00:46:25,830 –> 00:46:29,110
more likely to buy. And we can again propagate that
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00:46:29,110 –> 00:46:34,240
information into the marketing platform for subsequent campaigns that are
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00:46:34,240 –> 00:46:37,840
much more tailored to the interests of the customer. And it
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00:46:37,900 –> 00:46:42,070
helps us fulfill that brand promise in showing the customers
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00:46:42,070 –> 00:46:47,320
we value them, and we’re delivering on our commitment to
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00:46:48,410 –> 00:46:53,420
certain service levels. And we’re using this information to predict
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00:46:53,570 –> 00:46:56,880
how, when, and with whom to engage in all of
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00:46:56,880 –> 00:47:01,330
the various channels the customer would like to use. So,
703
00:47:01,330 –> 00:47:04,330
in the digital world, if everything is just digital, things
704
00:47:04,330 –> 00:47:06,620
are easy. In the voice world, if everything is just
705
00:47:06,620 –> 00:47:10,350
voice, things are easy. But when you start communicating across
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00:47:10,430 –> 00:47:15,010
channels, you need to blend that information in intelligent ways,
707
00:47:15,380 –> 00:47:20,270
utilize AI, and partner with vendors such as Adobe in
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00:47:20,270 –> 00:47:26,470
strategic ways to really deliver this empathy as a service
709
00:47:26,470 –> 00:47:34,440
experience as service. So Josh, we have some time for
710
00:47:34,670 –> 00:47:38,310
Q& A, and Josh is going to moderate that. But
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00:47:38,320 –> 00:47:40,520
we have some information here that you can take a
712
00:47:40,520 –> 00:47:45,560
look at as well. Thanks Dan. So we do have
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00:47:45,560 –> 00:47:47,460
a few questions that have come in already. So, as
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00:47:47,460 –> 00:47:50,570
a reminder to everybody in attendance today, to participate in
715
00:47:50,680 –> 00:47:52,640
our Q& A today just do me a favor and
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00:47:52,640 –> 00:47:54,830
submit those questions in the Q& A window below the
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00:47:54,830 –> 00:47:57,180
slides and we’ll get through as many as we can
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00:47:57,180 –> 00:48:01,080
with what little time we have remaining today. So first
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off, I’m going to ask this question. We’ll start with
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00:48:05,280 –> 00:48:10,190
you, Sridhar. So the question is, ” How do you see
721
00:48:10,190 –> 00:48:14,300
this solution evolving next?” What is the road map, I
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00:48:14,300 –> 00:48:18,710
suppose. Good. So the first thing we have done so
723
00:48:18,710 –> 00:48:21,950
far is to get the data from Genesys into the platform,
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00:48:22,000 –> 00:48:25,930
and then expose the information that an agent would need
725
00:48:25,930 –> 00:48:31,080
on agent desktop via lookup services and lookup calls. Next
726
00:48:31,080 –> 00:48:33,660
in our line of work is to get this data
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00:48:33,660 –> 00:48:36,680
and then provide some sort of analytical view back to
728
00:48:36,680 –> 00:48:41,300
Genesys. So information like how exactly the consumer, who was
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00:48:41,300 –> 00:48:46,040
dealing with this call center agent, navigating from a page
730
00:48:46,040 –> 00:48:49,710
or from a site based on interaction. Or things like,
731
00:48:49,710 –> 00:48:59,460
what exactly is the redemption rate, and are there other products
732
00:48:59,460 –> 00:49:02,540
that he could recommend which could actually make sense as
733
00:49:02,830 –> 00:49:05,340
a subsequent discussion. Those will be the next part of
734
00:49:05,580 –> 00:49:11,650
the road map. Thank you very much. This next question
735
00:49:12,020 –> 00:49:15,760
is for you, Alan. The question is, ” What can we expect
736
00:49:15,760 –> 00:49:19,870
in the way of change in a CX post- pandemic
737
00:49:19,870 –> 00:49:26,390
world?” I think the biggest thing that we can expect, and that’s
738
00:49:26,390 –> 00:49:30,390
a great question, is that this digital transformation, this accelerated
739
00:49:30,390 –> 00:49:33,960
digital transformation that was forced by the pandemic, is going to
740
00:49:33,960 –> 00:49:37,760
increase. It’s not going to go away. So when we look
741
00:49:37,760 –> 00:49:41,830
at the digitalization of business processes, brands, the cross- channel
742
00:49:41,830 –> 00:49:45,150
experiences, that’s all going to become more critical, and the
743
00:49:45,150 –> 00:49:48,850
ability to move that data across those different channels to
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00:49:48,850 –> 00:49:51,440
be able to give that integrated experience, which every customer
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00:49:51,440 –> 00:49:56,830
wants, is going to be the big shift in 2021, 2022.
746
00:49:57,240 –> 00:50:00,170
So that’s really what I’m looking forward to, is the
747
00:50:00,170 –> 00:50:07,300
new digital world that we’ll see exposed coming out. Thank
748
00:50:07,300 –> 00:50:10,600
you very much. Dan, I’m actually going to direct this
749
00:50:10,970 –> 00:50:15,390
next question to you and Sridhar, actually. So, during your
750
00:50:15,390 –> 00:50:17,960
demo, you were showing all of the interactions that you
751
00:50:17,960 –> 00:50:19,820
were putting in from the web page and then receiving
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00:50:19,820 –> 00:50:23,730
them on the back end. A attendee wants to know, ” Is
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00:50:23,730 –> 00:50:29,460
this using Adobe Analytics on the web page itself?” Yes.
754
00:50:29,460 –> 00:50:34,640
So, the new partnership that we’ve been discussing is about
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00:50:34,640 –> 00:50:39,370
the Adobe Experience platform integration, but we also integrate with
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00:50:39,670 –> 00:50:44,170
several other Adobe products, including Adobe Analytics. So we can
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00:50:44,320 –> 00:50:47,640
send information to Adobe Analytics and we will be able
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00:50:47,640 –> 00:50:50,810
to use the information that is in Adobe Analytics to
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00:50:51,030 –> 00:50:56,460
further inform us about the identity, the sales stage, of
760
00:50:56,460 –> 00:51:02,840
that customer. We integrate with Adobe Tag Manager, Adobe Launch.
761
00:51:03,010 –> 00:51:09,130
We can also integrate with Adobe Experience Cloud, and we
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00:51:09,130 –> 00:51:14,440
even have integrations through our, what we call data actions,
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00:51:15,990 –> 00:51:19,200
with products such as Marketo. So there are a number
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00:51:19,200 –> 00:51:24,440
of integrations that we have with Adobe products through this platform.
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00:51:28,780 –> 00:51:32,230
Thank you very much. The next question is, ” How do
766
00:51:32,230 –> 00:51:36,320
you carry context from web to voice without forcing customers
767
00:51:36,320 –> 00:51:41,770
to log in on the web?” There are a couple of different options, and we
768
00:51:41,770 –> 00:51:46,750
work together with Adobe to do this. So, we utilize
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00:51:47,710 –> 00:51:52,160
the cookie, the phone number, and the email to do
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00:51:52,160 –> 00:51:57,700
what we call identity stitching. Additionally, Adobe has something called
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00:51:57,970 –> 00:52:02,260
an identity service. So, as you saw when we were
772
00:52:02,260 –> 00:52:06,020
doing the demonstration, we started with an unknown visitor. So
773
00:52:06,020 –> 00:52:10,700
there still are insights you can glean from observing, analyzing
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00:52:10,790 –> 00:52:14,790
the behavior of people who are unknown. We can see
775
00:52:14,790 –> 00:52:16,320
what part of the world they’re from if they’re on
776
00:52:16,320 –> 00:52:19,590
the website, we can see what may have brought them
777
00:52:19,590 –> 00:52:24,380
to the digital property, we can observe what they’re putting
778
00:52:24,380 –> 00:52:29,440
in their shopping cart or what form fill elements they’re
779
00:52:29,480 –> 00:52:34,730
entering into an application online. And then once the customer
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00:52:34,730 –> 00:52:38,090
starts to share some identity information, we can begin to
781
00:52:38,090 –> 00:52:40,610
connect those dots. We can say, ” What do we know
782
00:52:40,610 –> 00:52:44,470
about them,” in the marketing automation platform once they’ve shared
783
00:52:44,470 –> 00:52:49,170
their email, maybe after initiating a chat. We can then
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00:52:49,250 –> 00:52:52,990
use that to see what other campaigns appeal to them.
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00:52:53,980 –> 00:52:56,070
And then, if they do share a phone number, when
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00:52:57,370 –> 00:53:00,810
that call comes in we can, in real- time, find
787
00:53:00,810 –> 00:53:03,060
out if the owner of that phone number is on
788
00:53:03,060 –> 00:53:07,840
our website right now, yesterday, last week, and again pull
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it all together. So, it is a solution we call
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00:53:14,530 –> 00:53:19,450
progressively profiling. So we don’t have to have the identity
791
00:53:19,450 –> 00:53:24,860
of all people known. This can evolve as a customer
792
00:53:24,860 –> 00:53:29,280
begins to share information by their behavior and by entering
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00:53:29,320 –> 00:53:36,430
some information online. Sridhar, anything else to add to that? Yeah, I mean
794
00:53:36,740 –> 00:53:38,650
you got pretty much everything. One thing I want to
795
00:53:38,650 –> 00:53:42,840
add is what we are looking at in terms of reacting
796
00:53:42,890 –> 00:53:47,470
or responding to a particular customer. Predictive engagement, as well
797
00:53:47,470 –> 00:53:51,260
as how we want to include all the marketing that is
798
00:53:51,260 –> 00:53:54,970
being done so far, and how we can actually transition into
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an action, whether it is engaging with a call center
800
00:53:58,530 –> 00:54:01,580
agent or engaging with a brand via other means. So
801
00:54:01,580 –> 00:54:03,500
putting them all together, we just want to make sure
802
00:54:03,500 –> 00:54:12,320
we are conveying the right message at the right time. Thanks guys. So
803
00:54:12,320 –> 00:54:15,210
we have time for one more question, so I’m going
804
00:54:15,210 –> 00:54:18,280
to ask the last question and then I’ll wrap up
805
00:54:18,300 –> 00:54:20,950
here today. So, the last question is, “Do you foresee any abrasion
806
00:54:20,950 –> 00:54:23,210
with members who do not want to interact with bots
807
00:54:23,550 –> 00:54:27,270
and proceed directly to a live person without giving a
808
00:54:27,270 –> 00:54:34,570
way upfront?” I think we can utilize our platform to, number
809
00:54:34,570 –> 00:54:39,210
one, learn about the attributes and behaviors of all those
810
00:54:39,210 –> 00:54:48,100
people who may dismiss the bot immediately. Maybe, over time,
811
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you might identify people who are from a certain geography
812
00:54:53,390 –> 00:54:59,170
or looking at certain areas of your website, and those
813
00:54:59,170 –> 00:55:03,620
people are much more likely to dismiss the bot and
814
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ask for agent, agent, agent. And then, in the future, you
815
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can start to put them into a segment for different
816
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personalized treatment. So, when we see people who share these
817
00:55:15,020 –> 00:55:19,470
attributes, connect them right to a live agent. And others
818
00:55:19,600 –> 00:55:23,340
may prefer to engage with bots, for example, and in
819
00:55:23,340 –> 00:55:27,170
those cases you may not want to, even though you
820
00:55:27,170 –> 00:55:29,860
would prefer as a business to connect them to a
821
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live agent, maybe you discover that the customer is more
822
00:55:33,240 –> 00:55:37,700
comfortable engaging first with a bot to see if they
823
00:55:37,700 –> 00:55:40,780
can get that information that they need much more quickly.
824
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Any other ideas there, Sridhar or Alan, you’d like to
825
00:55:45,880 –> 00:55:52,830
add to that? I, personally, have seen things whenever I
826
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need to get a, especially when businesses are having different
827
00:55:57,100 –> 00:56:00,420
mandates based on geographical locations, I would personally just would
828
00:56:00,420 –> 00:56:03,370
like to reach out and then get the information as
829
00:56:03,370 –> 00:56:07,790
quick as possible, so bots work in most cases. And
830
00:56:07,790 –> 00:56:12,680
again, what we’re trying to do here is utilize the
831
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behaviors and attributes, the data that’s available in our combined,
832
00:56:17,590 –> 00:56:23,730
collaborative platforms, to predict how, when, and with whom engage,
833
00:56:24,320 –> 00:56:30,180
so how to engage could be offering a callback, or
834
00:56:31,200 –> 00:56:36,390
a email, or again, suggesting a bot when you think
835
00:56:36,520 –> 00:56:40,000
that’s the best approach. So the AI has the ability
836
00:56:40,000 –> 00:56:45,990
to discover and learn those customer preferences over time. Right.
837
00:56:45,990 –> 00:56:47,570
The only thing that I would add to that is
838
00:56:47,570 –> 00:56:52,290
that we call that the contextualization of the experience. And
839
00:56:52,290 –> 00:56:57,120
so, that could be anything from you’re calling in from
840
00:56:57,120 –> 00:56:59,710
a mobile number so you don’t want to necessarily go
841
00:56:59,710 –> 00:57:02,540
to a bot, to there’s a back- end system that
842
00:57:02,540 –> 00:57:05,030
may have data, say it’s you’re calling in about a
843
00:57:05,030 –> 00:57:07,820
credit card breach and it already knows that your number’s
844
00:57:07,820 –> 00:57:11,820
been breached so it immediately sends you to a live
845
00:57:11,820 –> 00:57:14,730
agent. So, there’s some really interesting new technologies that are
846
00:57:14,730 –> 00:57:17,360
coming out out there, and the way Adobe and Genesys
847
00:57:17,360 –> 00:57:19,830
are putting this together, I think, is definitely near the
848
00:57:19,830 –> 00:57:26,660
forefront. All right guys, thank you very much. I think
849
00:57:26,660 –> 00:57:29,570
that’s a good way to wrap it up. So, first
850
00:57:29,570 –> 00:57:32,250
I want to thank our speakers for answering those awesome questions.
851
00:57:32,720 –> 00:57:34,870
Unfortunately, there were a couple that we did not answer
852
00:57:34,870 –> 00:57:37,160
aloud, but don’t fret. We’re going to follow up with
853
00:57:37,160 –> 00:57:40,270
you via email within the next few business days. However,
854
00:57:40,270 –> 00:57:42,940
if you’re looking for more of a prompt response, do
855
00:57:42,940 –> 00:57:45,860
me a favor and just email us at onlineevents@ genesys.
856
00:57:46,170 –> 00:57:48,680
com, no caps or spaces, with the title of today’s
857
00:57:48,680 –> 00:57:51,090
webcast in the subject line and we’ll be sure to
858
00:57:51,090 –> 00:57:54,870
get back to you as promptly as we can. All
859
00:57:54,880 –> 00:57:56,940
right, so to wrap up, don’t forget to take advantage
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00:57:56,940 –> 00:58:00,290
of the additional resources within the resource list below the
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00:58:00,290 –> 00:58:02,910
slides today. So, clicking on these will open up in
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00:58:02,910 –> 00:58:04,790
a new tab, and make sure you do so before
863
00:58:04,790 –> 00:58:07,520
today’s session ends. It’ll give you additional information on the
864
00:58:07,520 –> 00:58:11,330
partnership between Adobe and Genesys. Also, as a friendly reminder,
865
00:58:11,330 –> 00:58:13,480
if you could please fill out that survey that’s going to show up
866
00:58:13,480 –> 00:58:16,690
at the end of today’s webcast, we’d greatly appreciate your
867
00:58:16,690 –> 00:58:20,980
feedback. And with that, on behalf of Alan, Sridhar, Dan
868
00:58:20,980 –> 00:58:23,500
and the entire Genesys team, we thank you again for
869
00:58:23,500 –> 00:58:27,170
joining today’s webcast, ” Connect the Dots with Genesys and Adobe.”
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00:58:27,490 –> 00:58:29,470
Until next time, have a good one everyone.
