As we come upon a new year, marketers everywhere are considering their marketing strategies for 2018, and many are finally thinking about pursuing personalization programs. If you have put off personalizing your customers’ or prospects’ digital experiences thus far, it may have been for any number of reasons: you haven’t felt that your company was ready for it, it seemed like too big of an undertaking, you wanted to focus on other priorities, etc. But you don’t need to put it off any longer. The right technology partner can make it easy to get started.
In this blog post, I’ll walk through the high-level requirements for any personalization technology you invest in next year. There are, of course, many individual features and nitty-gritty details you’ll want to look for as well. You’ll want to figure out if any solution can integrate with your specific martech stack, and you’ll want to make sure it can help you accomplish your specific goals. But at the highest level, in order to deliver successful one-to-one personalization, you need a solution that is a complete cross-channel platform, contains a single profile for each person, operates in true real time, allows you to execute on your strategy without reliance on IT or engineering, and delivers robust and accurate attribution analysis.
For a more in-depth analysis of how to evaluate personalization technology, I also recommend you download our new full-length book, One-to-One Personalization in the Age of Machine Learning, for free. Let’s dive in!
1. A single platform to leverage across channels
The term “personalization” encompasses many different tactics and channels. Exit and cart abandonment messages, segment-based communications, product and content recommendations, account- and industry-specific experiences, web application, mobile app, push notifications, email, digital advertising, person-to-person, and search all fall under the umbrella of personalization.
Point solution vendors that provide tools for each of these individual tactics and channels have popped up over the years. It may seem wise initially to invest in a point solution, but it can become overwhelming (not to mention fragmented) as soon as you want to do more than that point solution was designed for. Soon you’ll find yourself with a jumble of unconnected technologies that you need to wrangle—each with a separate account and separate data.
It is much more effective and efficient to address all of your personalization needs with one single platform that allows for personalization across channels and tactics. While researching personalization technology, consider your potential future needs and find a solution that will grow with you — rather than limit you.
2. A single profile for every single person
It’s impossible to deliver an experience that is unique and relevant to an individual if you don’t have a comprehensive understanding of that individual. For example, imagine several different people observing a shopper in a physical store at different moments. Each person would notice the person taking different actions. If they didn’t share their observations, they would each have a very different view of that person’s preferences and intent. But once they put them together, they form a complete picture of what that individual is looking for at that moment and what his interests and affinities are.
In the digital world, successful personalization requires that all of your in-depth behavioral data from across channels be captured, synchronized with external attribute data, and brought together into a single profile for each visitor, customer and account. However, a single profile is not easy to deliver and hard to find among vendors. Many personalization vendors will appear to provide a complete platform that offers capabilities across the full personalization spectrum, but merging data sources is either impossible with their existing tools or very complex and time-consuming. It actually requires an integrated Customer Data Platform (CDP). Make sure you find a personalization solution that includes a CDP at its core and allows you to see a single profile for each person that interacts with your company.
3. The ability to act on any and all data in real time
We tend to be forgiving when anyone says that something is available in “real time.” We often take that to mean “quickly” or “soon” rather than the phrase’s real definition: “the actual time during which a process takes place or an event occurs.”
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In terms of personalization, “real time” refers to the actual moment that someone is interacting with a digital property. When we say that the data should be used to deliver a personalized experience in real time, we mean it should be delivered the actual moment a person is interacting with the company, regardless of the channel. All aspects of every visitor’s complete history must be combined with everything she is doing in the moment, and everything you’ve learned about her from all relevant sources, to deliver a personalized experience — in a matter of milliseconds.
The term is used liberally in many vendors’ marketing messages — and isn’t always meant in its full and accurate sense. Dig into any vendor’s capabilities to determine if it will allow you to instantly and undetectably deliver relevant experiences that leverage a person’s in-the-moment, not past, intent.
4. The ability to manage the platform without the need to rely on IT or engineering
You’ve probably experienced the pain that results from relying on other teams in your organization to accomplish your marketing goals. Whether you need assistance from engineering, IT, customer success, or sales, it can be frustrating when other teams — with their own priorities — fail to put your initiatives at the top of the list. When it comes to something as important as the customer experience, you don’t want to be forced to always count on others. So what can you do?
With a best-of-breed personalization platform, you and your team should be able to launch, measure, and adjust personalization campaigns quickly and easily on your own, without intervention. Yet the platform needs to be comprehensive enough to address all of your complex multi-tactic, cross-channel demands. With some vendors, a platform like this just does not exist. It’s a good idea to find out from current customers if the solution is easy or cumbersome to use.
5. Robust and accurate attribution analysis
Testing, analytics and attribution analysis are critical components of any personalization campaign. Without the ability to test, you cannot know if your campaigns are successful or if there is anything you can do to improve your approach. You need built-in testing and attribution analysis to iterate rapidly and ensure your experiences and algorithms deliver the best results possible.
Some solutions are not transparent when it comes to attribution analysis. Some vendors, particularly those with product recommendation tools, will provide reporting on campaign results but not enable customers to run or manage those reports themselves. And many will boldly claim that their “black box” solutions have made you hundreds of thousands or even millions in incremental revenue—taking credit for growth that may have occurred anyway. When selecting a personalization solution, make sure that you have the ability to compare the results of every campaign against control and that the solution utilizes sound statistical science for accurate and defensible attribution analysis.
Final Thoughts
If you’re evaluating personalization for 2018 for the first time (or if you’re reevaluating your existing tools), make sure that your personalization technology is a complete cross-channel platform, contains a single profile for each person, acts in real time, allows you to execute on your strategy without relying on IT or engineering, and delivers accurate attribution analysis.
To learn more about why these aspects of personalization technology are critical to delivering relevant, one-to-one experiences for your customers and prospects – and a whole lot more – download a free digital copy of our new book, One-to-One Personalization in the Age of Machine Learning today.
