What makes a marketing technology valuable is a question that marketers, analysts, entrepreneurs and enthusiasts grapple with on a regular basis. In most instances, there is no single answer but rather a case-by-case evaluation. But what if some technologies really are more valuable than others?
With constant change being the only certainty today and almost everything we are familiar with coming into question, businesses are adopting new processes, ideas and technologies at breakneck speed. Choosing what tool to reach for first in this environment has become crystal clear: the technology that brings the most value out of your data is the one you want first.
Don’t agree? Look no further than recent developments in the martech world to get confirmation. Today, more than ever, marketing technologies’ value is directly correlated to their ability to leverage data in different ways.
Think about Twilio’s recent acquisition of customer data platform provider Segment, where Jeff Lawson, co-founder and CEO of Twilio stated “data silos destroy great customer experiences.” Or Salesforce’s acquisition of Evergage earlier this year, aimed to improve website content personalization based on the realtime capture of customer behavioral data during a visit.
So let’s take a look at what a data-value-based mapping of the martech technology landscape looks like.
Martech’s Data Value
A few weeks ago, Chiefmartec editor Scott Brinker took the virtual stage as the keynote speaker in the Martech Conference. As part of his presentation he spoke about the value of data for marketers. He made the case for data value from martech solutions to be a function of their ability to distill data and help marketers act upon it using the chart below.
One interpretation of the chart is that the combination of changing dynamics, the faster pace of decisions being made, and the growing quantity of data have led to marketers being able to generate more value the more distilled and actionable a martech solution can make data.
This isn’t to say that every martech solution should aim to be at the top right corner of the chart. A lot of value can still be gained from a solution positioned dead center, or even at the bottom left corner. After all, martech is nothing more than an ecosystem composed of multiple pieces, all of which should generate value for marketing teams.
So what would a map of the different solution categories in the data value chart look like?
Related Article: Managing Your Martech Stack in a World of Constant Flux
Mapping Martech Categories by Their Data Value
The nexus of the data value chart would probably be ruled by the solutions in charge of acquiring and retaining the data that feed companies’ martech ecosystems. As seen in the chart below, solutions such as tag managers and data warehouses would be found here.
Solutions that allow marketers to understand and actively interact with the performance of campaigns, journeys and plans would be somewhere in the middle, similar to how we see customer journey analytics and BI Dashboards.
Point solutions, such as email service providers or mobile messaging platforms, would be to the far right, and based on each specific vendor, somewhere around the middle of the data distillation axis.
Finally, the top right corner would be reserved for solutions that provide marketers with both actionable knowledge and insight, as well as the ability to do something with those insights. Orchestration engines and personalization engines fit the mold of solutions that transform insights into action to intelligently adjust and impact brand-customer interactions.
It goes without saying that the engines at the top right need the solutions at the bottom left corner in order to capture the data needed to extract those insights. Similarly, they might need some of those messaging platforms to send out the ideal campaign based on the knowledge obtained. That’s probably why martech is referred to as an ecosystem, and is structured as a stack.
Furthermore, some may claim that solutions aren’t a “dot on the chart” but rather have a number of capabilities across the different dimensions of the data value graph.
As marketers continue to seek solutions to help them keep up with the ever-changing environment, they would be wise to consider the value each solution provides from the data they have as a significant factor in their decision making process.