{"id":354650,"date":"2020-11-24T20:00:12","date_gmt":"2020-11-25T04:00:12","guid":{"rendered":"https:\/\/www.genesys.com\/?post_type=blog&p=354650"},"modified":"2023-08-13T22:38:39","modified_gmt":"2023-08-14T05:38:39","slug":"use-predictive-engagement-to-cash-in-on-online-holiday-shoppers","status":"publish","type":"blog","link":"https:\/\/www.genesys.com\/en-sg\/blog\/post\/use-predictive-engagement-to-cash-in-on-online-holiday-shoppers","title":{"rendered":"Use Predictive Engagement to Cash In on Online Holiday Shoppers"},"content":{"rendered":"

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The busy holiday season is under way. And we\u2019re 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<\/a> 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.<\/p>\n

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Ramping up your digital concierge service to prepare for this traffic might seem more challenging than hiring additional in-store staff, but it doesn\u2019t have to be. In its report \u201cPredictions 2021: It\u2019s All About Empathy, Digital and Virtualising Customer Care,\u201d Forrester forecasts that retailers and banks will have hybrid store\/contact centre roles in 2021. This will become the norm \u2014 with brick-and-mortar staff using their skills and knowledge to provide digital support to customers.<\/p>\n

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.<\/p>\n

So, as more holiday shoppers rush to eCommerce sites\u2014 some for the very first time \u2014 you need to maximise conversion rates. Here are five ways predictive engagement can optimise your online sales strategy.<\/p>\n

1. Automate targeting eliminates manual efforts<\/strong><\/h4>\n

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\u2019s 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 behaviour 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 prioritise customers with the most pressing needs.<\/p>\n

2. AI identifies the right type of customers<\/strong><\/h4>\n

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

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3. Agents receive web session context<\/strong><\/h4>\n

With real-time tracking, agents see real-time session information on a customer\u2019s website journey<\/a>. 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.<\/p>\n

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4. Arm agents with omnichannel capabilities<\/strong><\/h4>\n

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.<\/p>\n

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5. Measure and report on conversion rates<\/strong><\/h4>\n

Predictive engagement intercepts customers who show potential to abandon the conversion funnel. It eliminates the cannibalisation 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 behaviour 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.<\/p>\n

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 analyse conversion patterns. This allows you to:<\/p>\n