Data Analytics

Central Question of Data:

What do customers want TODAY and how can we deliver it for them?

The Data Analytics Process:

  • Customer engagement
  • Analytics and reporting
  • Leverage analysis to generate dynamic, personalized content
    • i.e. In-app content, social media content, advertising content, email content, etc.
  • Utilize time and location-aware content to reach customers on a regular basis
    • i.e. Geo-Location & Geo-Fencing

Critically Categorize Datasets to Answer Questions About Customers/Potential Customers That You Didn’t Know You Had

  • Utilize these break-throughs to reach customers via their preferred mediums
    • Hit your consumers wherever they are
      • Push notifications within an app
      • Facebook and other forms of social media
      • Advertisements managed by 3 rd parties that target relevant places they visit on their computers/mobiles
      • Geo-Location based notifications/offerings/advertisements

Take the Complicated Story, Relate All the Variables, and Simplify It

The bottom line goal is to utilize thousands of data permutations to continually identify your company’s “core drivers” (in the eyes of your consumers). Then you have to determine the most effective way to aggressively and optimally “drive” those drivers (via more data that supports this determination) to each individual customer.

analyzing data analytics

Create a Streamlined System to Take Datasets and “Bring the Findings to Your Customers’ Experience”

  • Capture
  • Understand
  • Segment specific customer messaging
  • Personalize the messages to individual customers

Use the Data to “Listen” to Your Customers

  • What does the data tell you?
  • Look to uncover new ways to communicate with/reach your customers/potential customers
    • Engage audiences
    • Drive sales
team reviewing data analytics

Decrease Your Costs

The idea of cutting costs while salvaging capabilities is a business philosophy older than time itself. With technological innovations, cutting costs isn’t just a possibility—it’s an availability. Utilize datasets to determine the most efficient ways to communicate with and drive sales from your customers. Decimate your “cost per sale/cost per re-sale”.

For example: Many companies rely on one method (for example, email marketing) to drive resales or new sales. To make matters worse, many companies don’t even evolve their content/strategies in utilizing their one “go-to” method. Take a typical home insurance provider as a specific example. They send out an email blast 3 months ahead of a renewal data, then again at a month, again at a week, again at 3 days, again at the date itself—and they continue to try for a week, month, or two months post-date. Then what happens? They’re forced to hire a collection agency to “take a stab at it,” for an inflated price—and, oftentimes, utilizing the same method (i.e. email marketing) that the insurance provider tried in the first place. At no point in this process did the insurance provider stop to ask themselves how effective an email in and of itself was in the first place. Perhaps the non-renewed clients don’t prefer email? Perhaps they barely check their email? Perhaps the emails go to their spam?

Leveraging data to optimize both the content and messaging with which you reach your customers/potential customers is only half the battle. Optimizing how to effectively and consistently reach them with your provided content/message is the all-important other half that often gets lost in translation. Our analytics processes stress both sides of the coin equally.


Metadata, for the purposes of how we discuss it, gives you a “30,000-feet- in-the- air view.” It is essentially the data that describes underlying data. We utilize it to understand your customer connections. i.e. What types of people “talk” to each other, what people shop at similar stores/outlets, what demographics are more likely to be motivated by similar logic, etc.

Metadata is critical to establishing the “big picture” of your datasets to simplify what those datasets tell you.

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