For all the talk about the value of accurate data, few of us are making the effort to calculate the true and total cost of keeping data up-to-date and making it ever richer. Real-time updates, data overlays, metadata appends and other improvements cost time and money. How can we be sure our investment is justified? This question applies to most firms but it is especially important for information suppliers. They need an accurate idea of the “ROI” of the data they’re selling to their customers, and should understand the return on their own investments in building information repositories.
To calculate ROI, we must to look at both sides of the ledger sheet (decreased expenses and increased revenues). Then we compare that to the cost of the work.
Typical information investments fall into these categories:
Maintaining the accuracy of an existing database
- Telephone verification
- Internet verification
- Automated monitoring
Appending critical metadata
- Email and social contact appends for listed executives
- Firmographic appends (headcount, budget, revenues)
- Adding data on key decision makers
- Job function appends
Appending detailed intention data
- Expiration date of existing software licenses
- Announcements of significant future events (land purchases, rounds of investment under way, pending deliveries to important clients)
- Major regulatory milestones
- Surveys of purchasing intent
Expanding a database and overlaying in-house and third-party data
- Assessing market share (the universe of potential customers vs. your current customers)
- Broadening a database’s scope or adding information on new or adjacent markets
It’s fairly simple to measure the cost of each of these efforts. To calculate expenses, you just add up the checks you write to do the work. The ROI value is tougher to work out since you have to “back out” the effect of economies of scale (i.e., the bigger an organization gets, the lower its expenses per capita are) and general “rising tide” economic growth that would have happened without the investment. Once you’ve adjusted for these two factors, though, ROI calculation should be as easy as assessing any direct marketing effort.
- Better sales segmentation leads to more efficient marketing spend and higher sales
- Better decisions based on improved data analyses lead to cost savings and higher revenues
- Better sense of market shifts allows adjustments to the mix of products and services offered to meet future demand
The first of these is the simplest to measure. The strategic value of better decisions, however, may not be clear for some time and can be tough to pin a dollar amount to. This probably why folks don’t like to calculate ROI – the costs are always crystal clear and the returns are often not.
The imperative for defensible data-driven decision-making is not going to abate soon. Despite the inherent difficulties, we can all expect to have to “prove” data investments are worthwhile, and we need to get more and more granular with our justifications.