Say goodbye to ETL and hello to superior customer data activation
Marketers work hard at innovating omnichannel customer experiences that leverage data as their lifeblood — yet it’s common for the data activation layer to be a bottleneck in the marketing mix.
Effective data activation, simply defined, unlocks knowledge from your cloud data warehouse to become actionable by marketers within the end tools they use every day.
What it truly means to activate customer data
Great, reliable data should be a given, and it can be — except when it’s not. Data latency, inefficient workflows, and lack of a unified customer profile across the martech stack are just a few common pitfalls that can mar the best-laid plans. So what is effective customer data activation?
Effectively activating your customer data is at the heart of driving personalized, omnichannel customer experiences. So, before we get to how and why you want to activate your customer data, let’s touch on that first word: what do I mean by effective?
Effective customer data activation is that set of marketing activities orchestrated across your entire martech stack that, for the customer, creates a unified experience no matter what touchpoint or channel they may engage in.
Customer LTV is improved when optimal data activation works consistently to meet them, at any time, and wherever they are, with the right message for that moment.
Sounds simple enough, but if that’s the case, why do we still live in a world where, after a negative customer service interaction around a product we are unsatisfied with, we receive an email offering us the same product for less money than we paid?
Hopefully, this is the exception in your organization, but it does happen. Data drives the customer experience, and when that data is not synced, the right and left hands can cause frustration and even brand abandonment.
The role of customer data activation
What are the attributes of effective data activation and the common challenges to reaching that goal? For most modern marketing teams, data activation begins with their CDP.
The job of the CDP is to aggregate multiple data sources into a unified and actionable view of the customer. At its best, the CDP is a layer of orchestration that manages data between your martech stack — email marketing apps, Google Ads, Facebook, chat platforms, website personalization tools, etc .— and the data warehouse, like Snowflake.
But the landscape has become so complex, and demand for personalized experiences so high, that we are now seeing that activation itself must become a layer to ensure that great data really gets put to work.
And, because there are limits to CDPs, which we’ll discuss in a moment, the activation layer is coming of age to ensure your data management strategy really delivers the elusive customer 360 view, and that it can be easily pushed into multiple channels with minimum overhead.
Today, most marketing teams use a host of SaaS applications to perform myriad jobs in the customer experience; effective data activation means the highest quality data reaches all these tools quickly and efficiently.
Many teams still rely on data engineering for getting customer data out of the data warehouse, a latency that modern marketing simply can no longer afford.
Moreover, the activation of data within different applications may need to occur asynchronously: an email marketing launches a campaign at 5 a.m., the app has an in-app offer correlated to a live event that starts at 10 a.m., and social media pulse updates throughout the day. Sound familiar?
The challenge here is that the customer’s potential activity related to all this, which may include opening the email, clicking through to an offer, attending the event, making purchases, opting in for an offer, or making another purchase, needs to sync in real time.
As customers move along their journey, they break themselves into new segments based on behavior. You get the idea; marketers need a unified data foundation that they can access directly to avoid both latency and data fragmentation.
A world without ETL?
While marketing has had to rely on other teams to get access to data, strategies built around using a data cloud platform like Snowflake and a CDP like Simon to both segment audiences and activate customer data avoid the need to move data at all.
Expensive ETL and Reverse ETL processes are unnecessary when teams use a cloud data warehouse that lets marketers activate their customer data with no barriers.
Not to digress, but audience segmentation goes hand in hand with effective data activation; with direct access to real-time data (again, little to no latency because it doesn’t have to be moved), marketers can rapidly iterate campaigns and customer journeys as new information becomes available. Then, they can quickly activate it in the applications that reach those customers.
One example might be cart abandonment; with segmentation tools and live data, marketers could create a segment of abandoned-cart customers and send them an offer (as a nudge), while the completed purchase group receives a different offer or promotion.
With Snowflake and Simon at your fingertips, the segmentation and activation layers can almost become one.
For example, using Simon Activate, teams can quickly build advanced customer audiences by unifying data from their cloud data warehouse and all other sources.
In this case, marketers will want to ensure their CDP can resolve the identity issues that often arise with data from multiple sources; the onus is still on marketers to drive for that single, unified customer view before pushing out (activating) new communications.
Fortunately, AI is now on board to help, in some cases automating what was done by marketers and helping to drive efficiency and ROI on marketing spend.
Clearly, I’m arguing here for a zero-ETL approach to activating customer data; combined with no/low code activation tools, you can meet customers with relevant, timely experiences and more readily attain the ability to pivot, which is quickly becoming a must for today’s marketing teams.
