With a dizzying array of marketing technologies on the market today (over 5,000 last time we checked), it can be hard to know when, how, and where to invest your marketing technology dollars.
That’s why we’ve collected the top 6 signs that your next move should be to invest in your customer data unification layer — the one that sits at the foundation of your MarTech stack — instead of a shining new tool that uses data, but don’t help you unify all of it for all of your systems.
1. You can’t answer basic questions about your customers
Understanding your customers is the first step to building long-term loyalty and growth. Can you answer basic questions about customers like: how many of your app users are also loyalty members; or how many of your highest value customers do not have your credit card; or which customers bought holiday gifts in-store and online last month? If not, it’s probably because your data is siloed in disparate systems like eCommerce, point-of-sale, loyalty database, credit card usage logs, and app downloads, and you lack an interface where you can directly query your complete customer data. By unifying all this data, you can ask all your basic (and not-so-basic) customer questions, helping you to understand your customers and build meaningful marketing programs.
2. Your team uses ‘fuzzy matching” to resolve IDs
Fuzzy matching is an outdated technique that uses rulesets to connect customer records. Unfortunately, fuzzy matching alone is labor intensive to set up (which means new sources are often left out) and results in too many false positives and false negatives. This results in a large amount of wasted data. More effective ID resolution uses machine learning to power both deterministic and probabilistic matching, forming distinct databases for different use cases.
3. You can’t pull a customer list yourself
If marketers and analysts can’t directly build customer lists across all their unified data, there’s a problem. Teams need an intuitive and powerful interface to quickly and easily explore, segment, and use unified data about known customers to fuel personalized campaigns upstream. This interface should be built in to your customer data unification layer at the foundation of your MarTech stack.
4. Emails really aren’t personalized
Generic emails (non-personalized, non-targeted emails send to large portions of your email list) offer diminishing returns. The more such emails a brand sends, the more engagement tends to decrease. Over time, this leads to higher unsubscribe rates and declining revenues. This is because customers want emails that are relevant and meaningful to them, based on their own unique preferences. With high volumes of content in their inbox that has little to do with their interests, consumers tend to tune out.
In contrast, personalized emails that target specific segments and are triggered at just the right times get customers’ attention. Examples include: refill reminders to customers just when their products are likely to be running out, and personalized ancillary product recommendations for customers with upcoming travel. Bringing these types of campaigns to life is impossible unless brands have unified and connected all their customer data sources (POS, eCommerce, social, clickstream, and more) to their marketing automation tool or email service provider. Non-personalized emails are sure sign that a brands needs to invest in their customer data unification layer.
5. Product recommendations miss the mark
Getting product recommendations right is tricky. Without rich, unified customer data, you won’t be able to suggest the perfect next purchase. Therefore, if your recommendations efforts aren’t driving the engagement and revenue you want, take a good look at the data that fuels them. The more cross-source, unified data you feed into your recommendation engine, the better it will perform. Effective recommendations leverage complete customer records that contain point-of-sale and eCommerce transactions, email response data, clickstream data, and social interactions. Building these complete records as part of an effective customer data unification layer is a prerequisite to getting product recommendations right.
6. Omni-channel is a dream, not a reality
Omni-channel means seamless campaigns across multiple customer touch points like email, social channels, and your mobile app. For this to be possible, all known customer data sources must be unified and all touch points must be connected. And a slow connections isn’t enough. Data should flow rapidly through your systems so you can suppress customers from campaigns as they purchase the products you are promoting. An effective customer data unification layer not only allows you to syndicate data to many channels in tandem, but also enables suppression at exactly the right times.
Nearly every brand is trying to build unified customer views, but most haven’t gotten close. Major blockers include (but are not limited to) the scope and scale of customer data, the need for speed, and the intelligence required to resolve IDs without persistent, matching keys.
The Customer Data Platform (CDP) is the answer to the customer data unification problem (read the Forbes article). This technology was born out of consumer brands’ need to harness their own first party customer data. By unifying it and making it actionable, brands can craft the compelling, personalized experiences that today’s consumers have come to expect.