Customer Data Unification

Why Traditional Approaches to Customer Data Unification Fail Consumer Marketers

According to a recent Boston Consulting Group study, brands that create personalized experiences for customers are seeing revenue increases of 6% to 10% —two to three times faster than those that don’t. This is because customers now associate personalization with relevant and delightful experiences that help them accomplish their goals. Consumers are looking for online and in-person experiences that recognize them by name, recommend options based on their behaviors, and know their purchase histories.

Consumer experiences with internet-first brands are further increasing the importance of crafting thoughtfully personalized experiences.

Rising Consumer Expectations Driving Urgency

Internet-first brands such as Amazon, Airbnb, Spotify, and Uber are raising the bar on consumer expectations further. These brands have made consumers comfortable with the idea of sharing their preferences and purchase history in return for a frictionless shopping experience designed around their needs and likes. Consumers now have these high personalization expectations not just in their digital touchpoints but also their in-person experiences.

Given the opportunities, the expectations, and the highly competitive consumer landscape, you might wonder why more brands aren’t doing all they can to personalize their experiences. Turns out, they are. But a major hurdle stands in their way.

The Challenge is Customer Data Unification

Consumer marketers have struggled to use all their customer data to personalize experiences for years. A key challenge has been having real-time access to unified and usable customer data. While most brands possess the customer data that they need to power personalized experiences, this data is fragmented, out of reach, and impossible to activate. This is not a new problem, but it’s one that’s assumed higher importance now because some of the aforementioned internet-first brands are rapidly stealing market share and leaving many disrupted industries in their wake.

The challenges around customer data unification have persisted because traditional approaches to the problem are inadequate.

Traditional Methods are Difficult, Costly, and Incomplete

You might wonder why that’s the case after the many hundreds of millions of dollars that marketers have spent in trying to solve the problem. Here’s why:

  • Hard to Build: Most legacy customer data unification solutions have relied on slow and expensive schema mapping and ETL mechanisms. This requires either a long commitment of internal resources or the hiring of expensive consultants.
  • Hard to Maintain: These legacy solutions are hard to maintain as customer journeys and technologies evolve.
  • Hard to Scale: While legacy solutions can work with a small dataset, they struggle to deal with hundreds of millions or billions of records. This is especially relevant since marketers can reasonably expect to have to deal with trillions of customer records in the near future.
  • Deterministic: Legacy solutions rely on a deterministic approach that matches cleaned data across databases. This approach, because it isolates only the certain data, severely limits the usable customer data available to marketers.
  • Not Marketer-Facing: The legacy solutions are not marketer-friendly and marketers thus have to either spend an inordinate amount of time chasing data or compromise their own vision and ideas.

The High Cost of Status Quo

These data limitations mean that marketers often have a limited understanding of their customers, which holds them back from building customer experiences that deepen the customer relationship and help drive top-line revenue. This problem is exacerbated by the fact that the sheer volume of marketing data being generated is exploding because of better instrumentation, improved technology infrastructure, and a desire to know and shape customer journeys.

In my next blog post, I’ll discuss how an ideal solution to the customer data unification problem needs to have the scale to process the trillions of customer records and the intelligence to make sense of these records on an ongoing basis

Can’t wait for the blog post? You can learn more about Amperity’s Intelligent Customer Data Platform here.

We’d love to hear from you to discuss how we can partner in addressing your customer data opportunities. You can drop us a line here.

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