Digital Analytics / Business Alignment is Getting Better
I recently attended eMetrics Boston and was encouraged to hear a lot of presentations hitting on the idea of tying digital analytics reporting more directly to business outcomes, a topic we cover extensively in the Applying Digital Analytics class I taught after the show. This same kind of idea is also more popular lately in streams coming out of the eMetrics conferences in London and other conferences. A good thing, given the most frequent C-Level complaint about digital analytics is not having a clear understanding of bottom-line digital impact (for background on this topic, see articles here, here, and here).
Yes, we’ve largely moved beyond counting Visits, Clicks, Likes and Followers to more meaningful outcome-oriented measures like Conversions, Events, Downloads, Installs and so forth. No doubt the C-Level put some gentle pressure on Marketing to get more specific about value creation, and analysts were more than happy to oblige!
Is Marketing Math the Same as C-Level Math?
Here’s the next thing we need to think about: the context used to define “success”.
In my experience, achieving a Marketing goal does not necessarily deliver results that C-Level folks would term a success. And here’s what you need to know: C-Level folks absolutely know the difference between these two types of success and in many cases can translate between the two in their heads using simple business math.
Here’s an example. Let’s say Marketing presents this campaign as a success story:
Continue reading Does Advertising Success = Business Success? →
The following is from the October 2009 Drilling Down Newsletter. Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection? Just ask your question. Also, feel free to leave a comment and I’ll reply.
Want to see the answers to previous questions? Here’s the blog archive; the pre-blog newsletter archives are here.
Q: I have recently purchased your book Drilling Down and going through the many interesting concepts.
A: Thanks for that!
Q: I work for a membership Organization and we would like to conduct some analysis into who we may lose and approach them even before their membership lapses. But the only problem here is that we carry data only on the purchases made (though many of our members do not purchase our products and stay a member) and web site visits.
A: Are you *sure* that’s all the data you collect? I once worked with a professional membership org that thought they only had one data source, but turns out they had 8 – from 8 different areas of the org – that nobody really knew about.
Q: How do I know if a particular member is going to resign and lapse soon with this limited amount of behavioral data. Recently it’s been a concern that we are losing members who have been with us for more than 10 years and who are in their mid career profession (aged between 30 to 45) and indicated no specific reason for resignation.
This has been going on for the last few months and now we would like to strategically target these customers and approach them even before they react negative. What concepts could help me to do this? Your guidance would be much appreciated.
A: OK, my answer will be in two sections: if you (hopefully) find you have more data than you think, and if you really don’t have any other data to fall back on.
Continue reading Member Retention in Professional Orgs →