{"id":118313,"date":"2018-10-15T00:00:00","date_gmt":"2018-10-15T07:00:00","guid":{"rendered":"https:\/\/www.genesys.com\/?post_type=blog&p=118313"},"modified":"2019-01-03T13:26:46","modified_gmt":"2019-01-03T21:26:46","slug":"drive-real-value-ai-retail-contact-centre","status":"publish","type":"blog","link":"https:\/\/www.genesys.com\/en-gb\/blog\/post\/drive-real-value-ai-retail-contact-centre","title":{"rendered":"How to Drive Real Value from AI in Your Retail Contact Centre"},"content":{"rendered":"

[vc_section full_width=”stretch_row”][vc_row][vc_column][vc_column_text]Artificial intelligence. Machine learning. Predictive analytics.\u00a0Abstruse and technical? Perhaps \u2014 but you don\u2019t need to get into the algorithms to appreciate what they can\u00a0do<\/i>.<\/p>\n

The various flavors of artificial intelligence (AI) are making a difference across many areas of business \u2014 but perhaps most plainly in the customer contact centre. Because when applied to common customer problems, a little AI goes a long way. A chatbot can answer a hundred customers at once; an analytics engine can show you where the bottlenecks are in your processes; predictive algorithms can forecast what customers will do before they do it.<\/p>\n

Gartner predicts AI technologies will deliver $1.2tn of business value in 2018 alone<\/i><\/a>.<\/p>\n

Soon, the human agent may be refocused on more challenging tasks \u2013 relied on to deal with complicated escalations and provide humanity and warmth when it really matters. But the value of AI goes further than cost savings and resource efficiencies. The opportunities it opens up can change your entire business strategy for the better. Because the benefits it offers aren\u2019t incremental; they\u2019re paradigm-busting.<\/p>\n

The spoils of AI go to managers who recognise where these technologies can best be put to work. AI can help you hit even the most ambitious growth targets \u2014 while fundamentally changing your business for the better.<\/p>\n

Let\u2019s take a look at where that value can be added \u2014 and why it\u2019s not scary, but empowering. Here are some truths about the rise of AI, with some common myths exploded as a bonus.<\/p>\n

Make sure AI can intervene, not just interact<\/b><\/p>\n

The sci-fi version of AI is of a talking machine, humanoid or other beings. But the huge majority of AI in use today isn\u2019t focused on the spoken or typed conversation; it\u2019s deployed before that conversation begins, routing the call intelligently based on insights made from data.<\/p>\n

What does that involve? It\u2019s all about the data. Based on thousands or millions of data points, algorithms help you assess how customers behave in different situations, comparing situation A with situation B across many examples and seeing what causes or correlates. When a fresh call comes in, the AI is ready to use those learnings to make the experience smoother for the customer.<\/p>\n

\u201cCustomer contact centres are most efficient when they are able to automate routine tasks and quickly route callers to human agents who can solve issues in a timely and courteous fashion.\u201d\u00a0<\/i>\u2014\u00a0Communications of the ACM<\/i><\/a><\/p>\n

That might mean noting that a customer has ordered product X, and buyers of product X tend to make a first service call to the helpdesk between 14 and 21 days after purchase. So the AI routes that call to a technical agent with a record of handling such calls successfully. Or it might notice an out-of-pattern behavior from a major account, and pre-escalate the call so they\u2019re instantly put through to someone senior.<\/p>\n

What matters here is that it\u2019s the algorithm \u2014 the AI \u2014 making the decision. No human coder programmed its behavior. The AI is taking action based on what seems to have worked before. A lot of AI happens before a word is spoken.<\/p>\n

AI\u2019s ability to handle multiple conversations = KER-CHING for eCommerce<\/b><\/p>\n

Of course, AI technology can\u00a0\u2013 and does \u2013<\/i>\u00a0take part in the customer conversation. Many of the chat windows you see in service applications are \u201cmanned\u201d by software robots (bots), not people. They work best when a customer\u2019s queries cover a known set of subjects, because the AI can be equipped with an equally solid set of responses.<\/p>\n

(Keep in mind a large proportion of trouble tickets cover the same few subjects, again and again. You don\u2019t need a human agent to handle a simple password reset.)<\/p>\n

AI, of course, doesn\u2019t need a salary and won\u2019t get irritable when it deals with the same query for the thousandth time. But more importantly, an AI chatbot can deal with hundreds of customer conversations simultaneously.<\/p>\n

We humans may think a hundred people typing queries on their keyboards makes for a busy scene. But a computer\u2019s \u201cexperience\u201d of humans is that we\u2019re glacially slow and mostly absent, swooping in on rare occasions to type a few characters. Just as billions of people use Google daily, an AI chatbot can \u201ctalk\u201d to many customers at once.<\/p>\n

With companies\u00a0spending $1.3 trillion on over 250 billion service calls a year<\/a>, any firm that can integrate AI successfully to work alongside human agents is looking at serious ROI.<\/p>\n

Let retail customers serve themselves, and save big on resources<\/b><\/p>\n

Let\u2019s be blunt: the most successful service interaction is where your agent\u00a0never had to get involved<\/i>. Just as decades ago bank customers found they much preferred a quick visit to an ATM over waiting in line inside the bank, retail customers generally prefer self-service applications to phoning the contact centre.<\/p>\n

70% of customers prefer messaging over voice\u00a0<\/i>\u2014\u00a0IBM Watson<\/i><\/a><\/p>\n

That makes self-serve apps a high priority for the retail contact centre. But AI can do more than open a chatbot window. By \u201clearning\u201d behavioral patterns and discerning customer priorities, it can give the customer options and links likely to be of most use \u2014 designing and redesigning the self-service user experience on the fly, in a way that\u2019s invisible to the customer but of great utility to her. With a positive effect on things like cart abandonment and churn rates.<\/p>\n

Customers like self-service, because they feel in control. Business leaders like it too, because they can serve customers faster and more effectively at lower cost. With AI, it\u2019s a win for both.<\/p>\n

For the retail contact centre, AI is an ally, not a usurper<\/b><\/p>\n

Finally, let\u2019s make it clear that the rise of the machines doesn\u2019t lead to a downfall for the humans in your organisation. In fact, a major benefit of AI is as a\u00a0helping hand<\/i>\u00a0for agents, allowing them to be more effective in their work. Think of AI as more your trusted sidekick than overlord-in-waiting.<\/p>\n

\u201cAI will enhance their skills and allow them to move beyond routine tasks, like collecting and reporting information, to customer interactions requiring deeper insight and analysis\u201d\u00a0<\/i>\u2014\u00a0Forrester<\/i><\/a><\/p>\n

Just as AI-empowered self-serve apps offer the customer the right choices at the right time, AI in the contact centre can replace multiple screens of information with just the right data required for the call. It means faster handling times, greater empathy from agents, deeper shared understanding of the problem that shows customers they are through to someone who can really help.<\/p>\n

That all makes for a more effective \u2014 and happier \u2014 agent. And we all know the effect happy employees have on Net Promoter Score.<\/p>\n

AI is your competitive advantage, not your competitor<\/b><\/p>\n

There\u2019s huge confusion about AI and what it means for business. So being the manager who \u201cgets AI\u201d is a great plaudit. Why not become that go-to-person for artificial intelligence?<\/p>\n

The four reasons above are a start. But as a general rule, look for the business opportunity of any AI-based solution as well as the immediate practical outcome.<\/p>\n

If it saves money, requires fewer resources, improves KPIs or simply performs faster and smoother, great. But open your mind to broader and deeper possibilities. What if the AI-enabled application predicting the number of calls at peak times could also predict peak periods of demand for a certain product \u2013 informing your supply chain decisions as well as your customer service ones? Alternatively, imagine your AI not just managing your trouble tickets but learning from what they say, and recommending improvements to your basic business processes as a result?<\/p>\n

AI is learning a lot from data. But we can learn a lot from our AI. And the manager with a sense of what they can do \u2014 both now and tomorrow \u2014 is well placed to be the organisation\u2019s innovator-in-chief.<\/p>\n

Takeaways:<\/b><\/p>\n