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Four stages of marketing data: integration, discovery, delivery, insight management

PUBLISHED ON 17 JUNE, 2014

I was recently covering the importance of building your very own marketing technology ecosystem, fitting in it a varied collection of software solutions that every one of us should be able to align with his or her own vision and marketing strategy.

I have also mentioned a few alternative frameworks, and I believe we can take this a bit further by putting together our own “zoomed-in” perspective of a company’s “marketing information” needs.

The schema below borrows concepts from Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms 2014 (where a good distinction has been established between three broad categories: information delivery, analysis and integration), Chief Marketing Technologist’s Marketing Technology Landscape 2014 (drawing a clear line between “business intelligence”, analytics platforms focused on “digital” data, and dashboards) and Gartner’s Who’s Who in Interactive Visualization for Analysis and Dashboarding 2011.

We have also fitted every single piece of software we have come across over the course of the past few months in one or more of the following three circles, themselves representing:

• A focus on data integration and/or discovery built around data already available “on premises” and therefore mostly focused on offline, structured data (e.g. transactional data), be it a local, cloud-based or hybrid solution
• A strength in dealing with unstructured, “liquid”, mostly digital data subject to a “pre-collection” process (for the data is often unavailable prior to tagging or scanning content)
• A focus on delivery and performance management, irrespective of the nature of data. Communication prevails over exploration and data consumers replace data analysts as the primary target of these solutions. The accent is on people and data governance.

These broad criteria run parallel to the four stages affecting marketing data nowadays: Integration, discovery, delivery and (where existing) insight management. The higher up we go in this scale, the stronger the focus on people rather than data.

Of course, there is room for many a sweet spot in the confluence of these circles:

• Some solutions respond to very specific needs for offline-online integration taking digital, liquid data as a starting point (and bringing structured, transactional or CRM data into the picture as the “house guest”). Others do the exact opposite
• Some solutions are built with ease of data exploration in mind, though also facilitating the delivery task for the very analyst or “power user” in charge of the discovery process. Others may be much more focused on one task or another
• Certain vendors thrive at data integration, incorporating data discovery capabilities for the analyst and, in various cases, also providing a given set of delivery features (in the form of report automation or storytelling). We have deliberately avoided the complexity of a further split between integration and discovery (with certain tools directly jumping from integration to delivery)
• Some (Sweetspot included) are solely focused on the “human factor” of data: personalized dashboards, communication of insights, saving time through report automation, and working together as a team towards improving overall performance.

Needless to say, it remains the marketers’ task to ascertain which combination of products best serves his or her needs.

It is not hard to imagine that most players in a given industry will be likely to favor a similar approach as a result of one type of data being predominant over another (think of transactional data in banking vs. unstructured, social media-rich data in the management of consumer brands), or the existence of differing levels of stakeholders as a result of a given company culture (think of a stronger focus on data delivery in more data-driven cultures that promote the democratization of business metrics).

Final thoughts: Upcoming trends

Gartner’s own summary is perhaps the best starting point if we are to draw any conclusions: “governed data discovery” – the ability to meet the dual demands of enterprise IT and business users – remains a challenge unmet by any one vendor. Not surprising. It seems clear from our perspective that data discovery will not serve business users while it remains a time-consuming task with a steep learning curve (no matter how user friendly).

An interesting point is also raised (in Gartner’s Magic Quadrant) on the subject of “Scorecards” and performance management: Most companies do not implement true scorecard/strategy maps using BI platforms – they implement dashboards. They are hence relegated to the Corporate Performance Management (“CPM”) arena.

Is there, however, more distance between performance scorecards and dashboards than there is between dashboards and raw data integration? After all, “technical” and “human” factors are already coexisting under a single roof.

But perhaps the most evident trend, in these reports and beyond, is the fact that every single process is becoming simplified once again by a new generation of tools that the market struggles to categorize or easily label, but that early adopters are already leveraging to obtain serious competitive advantages.

All in all widely open for discussion. And it is a very interesting one.

Looking forward to hearing your thoughts.

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