Experience Personalisation Series, Part 1 : Data
Every digital marketer recognises personalised content as a crucial element in each customer’s journey toward conversion. In the most basic sense, personalisation is simply the use of customer information to deliver the right content for each visitor, every time—in order to get the business results you want.
At Adobe, we express this equation with a simple formula: “Data + Content = Personalisation.” In other words, the better you know your audience, and the better you know which offers you want to deliver when and where, the more relevant your content will be, and the more powerfully it’ll drive customer engagement and conversions.
Personalisation runs along a spectrum, from traditional large-segment marketing—which isn’t very personalised at all—through prescriptive profiling, automated message delivery, and targeted recommendations. At the “very high” end of the personalisation spectrum we find the latest innovations: sophisticated algorithms and machine learning generating entire websites and in-app experiences on the fly for each individual user.
In this series of three articles, I’ll explore the ways in which you can bring data and content together to create all these types of personalised profiles and user experiences.
Let’s start by diving into data.
Salespeople have been building profiles of their customers since the very earliest days of trade, when your local shopkeeper knew you by sight, and would recommend products you’d find useful. In today’s world of large-scale marketing, though, many companies rely on broad customer segments and outdated profiles to tell them which ads to serve—a wasteful approach in which thousands of irrelevant messages are ignored by customers every day.
To avoid this wasteful spending, your personalisation platform needs to provide tools that enable your understanding of your customer segments to adapt in real time—molded by new customer behaviours, location variables, referrer data, and other relevant information.
The first time you interact with digital users, you might know very little about them—nothing more than the time and touchpoint where you met them, perhaps, and which link they clicked. This tiny cluster of data acts as the initial seed of an ever-growing profile—a picture of each user that you build up over time as you interact with that customer on your website, on mobile, in store, and at every other touchpoint.
The more you learn about your customers, the more you can personalise the content you serve them—and the more able you are to adapt the profiles you have for them, the more quickly you can re-personalise as their needs change. That means reduction in wasted ad spend, no more friction with customers, no more ignored messages, and a much closer, more mutually trusting relationship with the customer; just like how it used to be at your local shop.
The data from your progressive profiles will provide a solid backbone for your content personalisation—but if that’s the only tool you use, you still won’t be taking advantage of a wealth of other useful customer data you already have. I’m talking about all the data that’s locked up in your customer relationship management (CRM) system, your internal systems—such as enterprise resource planning (ERP) and data warehouse (DWH)—and all your other customer information resources that aren’t linked directly with your marketing platform. You own all this data, so why not make the most of it?
Well, not so fast. Not all data is actionable, and data doesn’t automatically equal useful knowledge about a customer. That’s why your personalisation platform should allow you to upload this data, then combine it with other customer interactions to determine which of it will be relevant to your ever-growing customer profiles—and thus, which of it you should use to enrich your personalised marketing.
A toolkit with this ability will enable you to build truly unified customer profiles, not only around interactions at marketing touchpoints, but—potentially—around every interaction a customer has ever had with your business, in any context. More to the point, these tools free you from trying to prescriptively define your audiences based on correlations between data points. Instead, they leverage actual interactions with these customers to show you how to market to them in the future.
Thinking even bigger, you’ll be able to use this newly imported data in many other marketing contexts, beyond just personalisation—think analytics for reporting, content management for content individualisation, data management to enhance your on and offsite experiences, and campaign management for cross-channel campaign execution. This means you’ll want to be able to share this data with other groups throughout your organisation, as seamlessly as possible.
At Adobe we’ve been working hard to provide exactly these kinds of integrated capabilities. We’ve built the ability to define unified audiences into solutions like Adobe Analytics and Adobe Target, and provided core service capabilities like Customer Attributes—all of which eliminate the need for Frankenstein’s monster-like platforms built of multiple applications, datastores, APIs, and user interfaces; and make seamless sharing of customer profiles a point-and-click reality.
With a powerful solution for gathering and integrating data into robust, adaptive customer profiles, you’ll have one major piece of the personalisation puzzle. But two big questions remain: How can you make sure the right content gets served to the right profiles? And how can you bring data and content together to create innovative customer experiences?
Those are the questions I’ll be tackling in articles two and three of this series. See you there!