Analytics at the Marketing/Finance Interface

Jim Novo is right about the relevance of financial data to marketers. There’s a wealth of information in those transactional records, and most companies don’t have analytics practitioners embedded within those departments.

Just as reporting (reportage) isn’t analytics, accounting isn’t analytics. There’s something to be said about the parallels between finance and analytics. Both have prediction, definitions, jargon, simulation, machine learning, ratios, rules, laws, and statistics. Both become confused with bookkeeping and dashboarding. One is older than the other.

If accounting/finance is an 110 year old, marketing analytics is 18.

There are very specific rules in bookkeeping, handed down for centuries. There are very specific standards in finance, handed down since at least the Renaissance. Should we be so lucky in marketing reporting, web analytics, analytics, and marketing science.

(Indeed, the very fact that marketing science has to add the word ‘science’ says something about how young the field is (founded in 1961). It’s called ‘chemistry’, not ‘chemical science’, after all.)

So there’s that axis and distinction – between counting and reporting, and analysis and prospection. Pretty solid ground there.

Marketing analytics becomes more complex because of the mixing of transactional data with attitudinal/behavioral data.

There’s a whole set of data that most finance people don’t have to think about. Certainly, in certain spheres of finance marketing, ‘psychology of the market’ starts to play a role. Those are some pretty early days. I’ve met only two of them. And it would appear that they’re in a super minority.

Jim Novo, in a previous comment thread, wrote: “Marketing history is full of examples where Awareness did not turn into revenue.”

I can think of many investments that did not turn into revenue as well.

It would appear that both disciplines are united in many ways.

The professional who tries to bridge this chasm, between marketing and finance, can be successful. But they’ll have to recognize two things:

• They will have to make the distinction between accounting/reporting and finance/analytics very quickly.

• They will have to make the distinction between transactional data, behavioral data, and attitudinal data, very quickly.

It’s worth pursuit.