Digital measurement has come a long way, from the earliest site counters to sophisticated multi-channel analytics tools; and from measuring simple page views to tracking event/engagement conversions. For today’s digital marketers, measuring “conversions” seems to be the end game. It’s like we’ve finally found the Holy Grail of digital measurement and now everything that we do is to “optimize conversions.”
But we forget that the true indication of marketing success is the increase of sales/leads. Hence, the next phase of digital measurement should move beyond conversions by tying it to sales.
The Digital Data Silo
However, linking digital data to sales is no small feat due to the challenges below:
- Digital and sales data sit in different tools and databases.
- The unstructured nature of digital data makes it especially hard for integration.
Let’s examine the first challenge. Most marketing departments probably utilize web analytics tools like Omniture, Google Analytics, Webtrends, etc. to measure digital conversion. But the sales data usually sit in internal business intelligence tools like Cognos, Business Objects, Teradata, etc. Trying to match datasets across different tools is no doubt a hassle for many marketers.
But if we tried to integrate the datasets, we have to decide, is it easier to bring digital conversion data internally or take sales data and import it to the digital analytics tools? If the marketing team decides to bring the digital data internal, then they’d have to request the help of the business intelligence, or God forbid… the ever-helpful IT team. If marketers decide to take the sales data external, then we run into an integration issue, because sales and digital clickstream datasets do not have a single primary key linking them together. No matter which way, it’s a fairly technical problem that I’m sure no marketer would ever want to deal with.
The Solution: Baby Steps
In order for us to move to true digital marketing accountability, integrating digital and sales datasets is inevitable. There are certainly some challenging technical issues at hand, but we do not have to tackle them all at once. Instead, we could take baby steps and conduct integration with the resources that we have on hand. Below is an integration road map that we can follow:
Obviously, the more data sources that we have to integrate, the more technically challenging it’s going to be. So if we focused only on a few key initiatives at first, we can start the integration process with simple tools that we’re all used to as marketers. For example, if we wanted to integrate the consumers who registered on our website to consumers in our sales database, then we can manually use Excel to complete the task. Moving up on the data sources ladder, if we wanted to attribute the internal leads data to a particular digital media channel, we can use the integration tool kits from Omniture or Webtrends. These tools allow marketers to import sales/leads data from Excel or through their API. Lastly, if your organization and marketing place a very strong focus on marketing attribution and data integration, then a full-scale marketing data integration project would have to take place. The implementation would probably take more than a year and would span across multiple departments.
Digital is a fast-changing world, with new tactics and channels emerging rapidly. Without tying our measurements to the bottom line, marketers have no clue which new tactics or channels are effective. Hence, as digital marketers we all need to get a little more technical and push the measurement beyond conversions.
Marketers need to know what’s in their data and trim out the filler to provide continuous, data-driven ROI for their brands.
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