Dismantling Data Silos for Great Customer Experiences

App deck graphic

Configuring, or even understanding your customer data as a whole can feel a bit like building Ikea furniture. Nothing seems to fit together, captions are in a language you don’t speak, and somehow you ended up with extra pieces (which both terrifies and confuses you). Marketers who started their careers in a time where writing ability and creativity were the most important skills they could have are now being asked to become pseudo data-scientists. 

Customer data is king, and it’s become paramount for business leaders to have it collected, understood, and acted upon for better customer experiences. But, how are non-technical marketers supposed to approach a challenge so heavily rooted in technology? They could involve their data science team (if they have one), but that comes with the typical pitfalls of getting two entities to work as one and maybe build an in-house solution. More often than not, it drains engineers and doesn’t function exactly as needed. They could also buy a whole alphabet of martech tools (CDPs, ESPs, DMPs, etc.), at the risk of creating a fragmented tech stack. So, what’s the solution that allows marketers to dismantle data silos and act upon valuable customer data? Let’s examine the possibilities offered by the Customer Data Activation Platform.


The first step to getting a holistic view of your customers comes from re-routing data into a single source. Not just demographic data into a CRM. Not just messaging records from an ESP. We mean any and everything there is to know about a customer. A Customer Data Activation Platform is similar to a CDP in the sense that it gathers and rationalizes data. The CDAP (let’s abbreviate from here on out, if you don’t mind) ingests data through APIs, SDKs, and cookies to build a Single-Customer View. It’s important to pull in CRM, transactional, and behavioral data, but also less recognized touchpoints like customer service channels. Having every possible method of data collection accounted for is arguably the most important foundational piece for crafting relevant messaging later down the line.


Now that you have your data consolidated, you’re one step closer to the dream of 1:1 messaging, but you’ll need a little help to get there. Luckily, marketers don’t have to handwrite messaging for millions — Artificial Intelligence and Machine Learning are here to fill in the gaps. In layman’s terms, AI can process and make sense of your vast sea of customer data, while machine learning makes meaningful connections through analyzing millions of customer’s data and behavior. These hefty data-science tools are the only way going forward to realistically be able to deliver upon growing customer expectations. But, be forewarned. Many solutions have attempted tacking on AI, or rules disguised as AI, to capitalize on the buzz. The best advice we can give is that during sales processes, bring your data scientists on board to truly determine if a platform is AI-first, or just AI-added.


Now that all the behind the scenes work has been taken care of, marketers can get to what’s always been most important: delivering exceptional customer experiences. The best way to go about this is to find a platform that’s all-in-one. For example, Blueshift’s CDAP collects data, runs it through AI/ML algorithms, maps out self-driving customer journeys, sends messaging off to the proper channels, and collects feedback all in one single platform. It has quite literally become a one-stop-shop for marketers, at businesses of all sizes, who want to dream up an ideal campaign (filled with personalization) and execute upon it as quickly as possible. The issue with having multiple platforms to do data collection, journey planning, and personalization is that things may get lost in translation (not to mention the headache those different bills will give your finance head).