Use Predictive Engagement to Cash In on Online Holiday Shoppers

The busy holiday season is under way. And we’re set for bumper online sales, as consumers choose the web over brick and mortars because of COVID-19 precautions. In fact, the U.S. Commerce Department reported new online retail sales data for the first half of the year grew from 11.8% in Q1 to 16.1% in Q2. And Genesys integration partner Adobe expects holiday spend to increase 39% this year.

online shopping

Ramping up your digital concierge service to prepare for this traffic might seem more challenging than hiring additional in-store staff, but it doesn’t have to be. In its report “Predictions 2021: It’s All About Empathy, Digital and Virtualizing Customer Care,” Forrester forecasts that retailers and banks will have hybrid store/contact center roles in 2021. This will become the norm — with brick-and-mortar staff using their skills and knowledge to provide digital support to customers.

This shift will bring an influx of traffic to your website over a very limited period. It is impossible and unviable to provide an optimal one-on-one chat experience to all these customers for this seasonal spike without using a combination of bots and web chat agents.

So, as more holiday shoppers rush to eCommerce sites— some for the very first time — you need to maximize conversion rates. Here are five ways predictive engagement can optimize your online sales strategy.

1. Automate targeting eliminates manual efforts

Web chat tends to be either reactive in which a chat offer persists on the page, or proactive, where chat is triggered based on static rules. But there’s a more time-effective way to engage prospects on your site. The next generation of chat is predictive; it leverages artificial intelligence (AI) to eliminate the manual efforts of creating and maintaining rules in a fast-paced digital landscape. Plus, AI continuously learns and adapts to visitors behavior on your website. In Predictive Engagement a flow route can be deployed that can route to a bot and then progress to an agent if the query is not addressed or straight to a web agent allowing the business to prioritize customers with the most pressing needs.

2. AI identifies the right type of customers

Predictive engagement outcome prediction models are designed to extract actionable insights from large amounts of web traffic. By analyzing the meaningful patterns of web behavior, our AI models can identify customers with the highest propensity to leave your website or call the contact center for help. Additionally, you can augment these insights with contextual segments to ensure that high-value prospects are prioritized. This means agents can engage with them at the right moment for maximum effect.

 

 

3. Agents receive web session context

With real-time tracking, agents see real-time session information on a customer’s website journey. They could use this information during a customer check out to detect errors, such as the use of an incorrect discount code or delivery address issues.

4. Arm agents with omnichannel capabilities

Genesys Predictive Engagement features an extra tab on the agent desktop to show all customer journey context. However, the overall agent experience maintains the same layout so agents can switch between channels seamlessly. Genesys Predictive Engagement handles two to three chats. Having visibility into the customer journey lets agents quickly troubleshoot issues or offer quick advice so customers can continue to self serve on their online journeys.

5. Measure and report on conversion rates

Predictive engagement intercepts customers who show potential to abandon the conversion funnel. It eliminates the cannibalization of sales, i.e., customers who would have self-served and bought online without the need for a chat or bot interaction. The Predictive Engagement sequence learning algorithm targets customers who are exhibiting behavior to complete a sale but their probability to complete the sale drops because of events such as dwelling on a page or question or browsing to a page not in a linear path to convert. The machine learning model works on a 30 day training cycle ideal for seasonal events such as the Holiday season.

The Genesys Predictive Engagement SDK easily syncs with existing reports on Google Analytics and Adobe Analytics to show where web chat was triggered on the journey. You can then analyze conversion patterns. This allows you to:

  • Generate conversion funnels
  • Create page reports
  • Segment web chat interactions
  • Build attribution modelling

Genesys Predictive Engagement is the ideal digital concierge service to deliver personalized experience for your online customers. With an increase in online holiday shopping traffic, it will pay to move from proactive to predictive. You’ll know exactly what to offer (bot or chat) when it matters. And you can measure it all.

Get ready for increased holiday activity with Genesys Predictive Engagement.

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