The holiday retail data goldmine: Unlock personalization at scale
As consumers start to open their wallets for holiday shopping, there's a complicating factor for retailers - how well do they know their customers?
Not well, as it turns out. According to Twilio data, 81% of companies say they deeply understand their customers, but only 46% of customers agree. For most businesses, customer data is simply too fragmented and can’t be activated for true personalization.
That makes the holidays challenging. This is exactly when brands want to leverage all the data they have collected throughout the year — such as purchase history, loyalty program status, and buying behaviors.
Too often, that data is just sitting in data warehouses. Meanwhile, customers are clicking around on e-commerce websites, trying and failing to find the perfect gift.
To convert those clicks into buyer’s journeys that end with completed purchases and happy customers, brands need to embrace personalization. Digital personalization enables retailers to increase conversion rates and reduce cart abandonment by delivering recommendations tailored to each user’s preferences and history.
Doing this effectively during the holidays depends on collecting and unifying customer data throughout the year. If you haven’t already, get started on these key steps now:
1. Unify customer data
Instead of a unified, coherent portrait, most companies’ customer profiles are more like a Picasso, showing a slice from customer success, a slice from sales, a slice from product interactions, a slice from the holidays, a slice from the summer — and none of them particularly connected.
Marketers and retailers might have to use half-a-dozen different dashboards to see different slices of their customer set. Fortunately, you can reassemble Picasso-like customer data into a more realistic, unified picture of customers.
Customer data platforms (CDPs) do that by aligning data in various applications and data warehouses and creating unified profiles for each customer that draw from data across the entire organization. The goal is to build a 360-degree view that connects real-time data like web traffic and mobile app data, purchase history from data warehouses and CRMs, and communications data from previous interactions over email, voice, SMS, web chats, and WhatsApp.
2. Leverage AI for next-level personalization
Once customer data has been unified, retailers can leverage AI to surface insights and create personalized activations. This goes beyond product recommendation to displaying relevant offers and discounts in real time, notifying consumers about products they’d like, and delivering personalized messages when and where they’re most effective for each customer.
Consider this scenario: A consumer goes to a retail website or app and clicks around a set of catalog items. Armed with real-time data, the app knows what they purchased in the past and what they’re likely to purchase this time.
It might offer a discount or suggest a premium product to nudge them towards completing that purchase. If it’s an anonymous shopper, the app can examine what other consumers like them typically buy based on what’s known about their location or behavior.
Imagine, further, that the consumer has the ability to send a message in real time and get a quick, personalized response from the app or website via whatever channel they prefer — SMS, web chat, or in-app chat.
Eighty-six percent of consumers say that being able to message a brand in real-time increases their likelihood of completing a purchase — but 72% feel their time is often wasted by brands due to slow replies. Imagine how much conversion rates would go up if retailers could respond in an automated way in real time.
3. Block the bots
Unfortunately, bots are a big problem for marketers. Between 14% and 30% of clicks on paid advertising campaigns are fraudulent, with 40% of that attributable to bots.
These automated software programs simulate human users, sometimes going so far as to create fake profiles on retail sites using synthetic identities. You don't want to spend your ad dollars on fraudulent identities, so it’s important to distinguish between living, breathing humans and automated algorithms.
Fortunately, having good, unified data on each customer helps you sort out the bots, enabling you to focus your advertising and retargeting campaigns where they will make a difference.
Looking forward to conversational commerce
Taking the three steps above will help you prepare for the holidays, as well as set you up for the next generation of retail, known as conversational commerce.
Over the next few years, the most advanced retailers will go beyond AI-powered recommendations to agent-powered, real-time conversations. For instance, a shoe brand’s app might reach out to the consumer proactively to say that a new shoe they might like just dropped — based on its analysis of data such as past purchases and shopping behavior.
If the consumer wants to buy the shoes, they can reply “buy,” and the agent will complete the purchase, bill their credit card, and ship the shoes to their address.
It’s also possible that consumers will converse with retailers via agents that shop and purchase on their behalf. Retailers of the future must be prepared to add chatbots and agents to the list of communications channels that they use to stay in touch with their customers.
Unifying data, leveraging AI for personalization, and eliminating bots will put your commerce house in good order, and set you up well for the next few holiday seasons.
Thomas Wyatt is president of Twilio Segment.
