Data Strategy Drives Marketing Outcomes

Tough economic times often mean reduced marketing budgets. Free up your MarTech budget by taking control of your customer data, storing it in a single, easy-to-access place, and using machine learning to uncover valuable insights.

These three steps will help you unlock your company's budget and approach marketing like the investment it is:

Step One

Own your customer data. Every interaction is an opportunity to gather data about your customer:

When a bricks-and-mortar purchase is made, capture the customer's data using a loyalty program. Don't have one yet? Use tender data with a bureau provider (like Transunion or Equifax) to generate PII.
Leverage an analytics suite like Google or Adobe Analytics to capture online behaviors.
Use customer service interactions to collect information and direct qualitative feedback.

Step Two

Centralize the data. Do the hard work to pipe all the sources above into one central repository that can be leveraged for all customer insights. This is the most critical step to driving insights.

Bureaus often don't share specific personal identifying information (PII) due to competitive and regulatory reasons. That's okay. Instead, take a federated approach to customer identity by combining various identifiers as attributes of your customer profile. The more identifiers a profile has, the higher your confidence in the identity will be.
Google and Adobe Analytics are notoriously difficult to pull the data out of. The trick is to avoid the obvious approach of exporting everything at once. Instead, create discreet exports of data assembled into sensible schemas. If it makes sense being exported as a spreadsheet, it will make sense in your customer 360 data warehouse (C360).
Enhance your C360 by incorporating qualitative data from surveys, NPS, and direct customer feedback. Social media is a treasure trove of information that can be extracted using enterprise-grade tools like Sprout and Sprinklr, or by building your own solution with an AI scraper like browse.ai.

Step Three

Finally, you can unleash the power of machine learning on your centralized data store. The bullets below can be endless. Whether you want to create a recency/frequency/cost model to personalize products or tailor offers to encourage a purchase, with unified data, the possibilities are endless.

If you'd like a deep dive on any of these steps or tactics, drop us a line at claroainews@gmail.com.