Why the Data Attribution Ecosystem is Broken — and How to Fix it

The data status quo currently looks like that mass of cords living in your basement that needs combing through.
July 20, 2018
Mikel Chertudi

The data status quo currently looks like that mass of cords living in your basement that needs combing through. A collection of all possible marketing metrics and experience data from siloed systems like ad platforms, analytics, and marketing technology placed into a data warehouse where they are then supposedly meant for action. And it’s fundamentally flawed.

Experience data strategy

Data strategy should be the first step — and usually isn’t — especially when looking at experience data.

 Complete experience data involves three critical components

  1. The person interacting with the experience
  2. The experience touchpoint described by both channel and content metadata
  3. The metric that represents the person’s interaction with the experience (impression viewed, link clicked, digital conversion completed, call made, store visited, etc)

Marketers have become complacent with just a few touchpoints reflected in the data — the status quo. There’s more consumer journey data available to a marketer than ever before; why take the risk of missing key metrics that could provide the alteration your business needs to function at a higher level?

Optimize through visibility

The more complete visibility you have into the combination of channel content, and interaction metrics — deepened by additional metadata and classifications — the better the opportunity exists to optimize both channel and content elements, and drive ROI. Being able to provide more personalization not only meets the needs for today’s savvy consumer, but it allows you to optimize for a superior customer experience.

The problem with today’s data

Unfortunately it’s not just the amount of data available that presents a problem. The integrity, aggregation, and analysis are tied up in the antiquated systems, leaving data analysts and digital marketers hoping that the data they’ve received is accurate. Technology is too sophisticated to let this happen, and yet the same complacency present in what data is provided is present in what it looks like, where it comes from, and what it means.

If you’re the person tasked with tracking campaigns and measuring their efficacy, you must look at the systems put in place for those campaigns. If you’re currently piecing together data from multiple sources, trying to understand a potential customer’s first touchpoint, the point of consideration, and the moment at which they convert, then you’re working too hard.

Strala does the work for you, and it does it more completely than any other platform in the industry.