Marketing has met IT, and thus far they are on speaking terms, though nothing lasts forever.

I was party to a discussion in which CMOs disclosed what is most vexing to them, and the answer in a walnut shell is data. The promise of digitally tracking leads, automating prospect management throughout the pipeline, big data with supplemental data, and laser sharp analytics is not coming true for most. Truth be told, many are not yet at the starting line.

Data, like iron ore, is eventually useful but mining and refining it is dirty work.

The problems at this stage of marketing evolution are many, and they provide good check lists and warning signs for CMOs with a hankering to engage IT (who will make many of these items painfully clear).

Not everything is digital: Though much of a customer’s buying behavior can be digitally mapped, much cannot. Your brand, non-digital advertising, word-of-mouth and other factors will create leads that have no source. Getting those elements into your big data dreamscape may not be possible.

Integration will never be complete: We are talking about mapping a complex array of different interactions from both digital and non-digital sources. IT time and budget is limited. Thus, there will never be 100% marketing intelligence/automation integration. Most enterprises are not even at 20%, and some SMBs may be in negative territory.

Automation will always be incomplete, and may get worse: You cannot automate everything, as government health care exchanges are proving (most tell applicants to “call us”). Some of the best marketing automation suites still rely on people to manually update customer interactions touch points in a database, and this has always been a problem even in CRM’s earliest days.

External data integration and benefits will hit, miss, hit, miss: Much of the potential value from “big data” is integrating external sources, as recent NSA leeks have proven. The data you directly collect will be more useful once combined with external sources … if you can find the right ones, have the budget to integrate them, and can make good use of the analysis. Many ifs and no guarantees. It’s your budget, but only you know how much of a gambler you are.

Analysis and knowing what you don’t know: Big money is being made in “big data” by a handful of firms Hoovering up all available data scientists and building expensive analytics frameworks. This shows that having data (even if you can collect, rent and integrate it all) is meaningless unless you have the chops for analyzing it all. Most companies don’t even know what they don’t know, so finding the big payoffs begins by recruiting data gurus and investing in ad hoc and structured analysis tools.

The promise is real but as elusive as an IRS who has your interest at heart. Like all complex problems, begin with small and obtainable actions that deliver a measureable benefit, and then move onto the next phase.