I've been reviewing two separate data lines (a term borrowed by biotech, I think. A data line is an amalgam of several very similar data sources in order to see greater patterns than could be observed from a single data source) NextStage keeps current -- financial institutions and higher education -- both for existing clients and because you never know when being able to drop an interesting statistic might come in handy at a dinner party.I haven't checked through NextStage's other data lines (okay, I check through our own data line regularly but a "one source" data line is more indicative of that source than the vertical or industry that one data source is in, as noted above) to see if this is unique to a vertical or something broader. I suspect that I'll check ePharma next.
Here's my curiosity; where is everybody?
Let's say you look at a given vertical and you have 10-20 data sources contributing to the resulting data line. Let's say that you know there's a given population that moves among all sources in that data line (an example would be all mature males with histories of cholesterol problems. That population will probably visit lots of pharma sites offering statins).
Next let's assume you have a good idea of the number of conversions (and for the purposes of this example we'll further hypothesize that all the sources contributing to the data line have a similar concept of "conversion", just to keep things neat and simple).
Okay, then, given the above, where is everybody? More to the point, where are all the conversions? If you know the population is X and you know that population is fairly stable and static across all data sources, and you know that what the separate sources are offering is a requirement as far as that population is concerned, you should be able to see a fairly healthy (forgive the pun) percentage of X converting.
I know what I will do to research this. I'll contact the companies contributing to our data lines and ask what their total real conversion numbers are (and here I'm defining "real conversions" along the lines of unit conversions regardless of conversion channel. Kind of "your offline and online and whatever else numbers have to be equal to or greater than a calculable percentage of X").If so, another question arises; Is there a model that defines products and services that will never convert well online?
If not, the question becomes "Where is everybody getting what they need?"
My thinking is that this is solvable if you increase the frame.
I'm curious to know if others have noticed something similar or can suggest another model for inquiry as I have little doubt this problem has been solved in some other paradigm.
Thanks.
Please contact NextStage for information regarding presentations and trainings on this and other topics.
I'll be speaking at the Society for New Communications Research Annual Awards Gala Summit on 1-2 Nov 07 in Boston. Come on by and say hello.
Riiiiiggghht.
What's a Q-bit?
Seriously, what is a conversion for the purpose of this conversation? If a conversion is a completed sale or even a sale agreed to in principle, there are plenty of goods and services that will not 'convert well'. Surgical services, auto sales (most people need to sit in the car or a comparable model to commit to a purchase), non-bulk sales of small $ commodities (I would not buy one 3" bolt online), non bulk sales of perishable commodities (e.g., one gallon of milk) (the delivery cost makes purchase of small cost items is too significant respectively compared to the 'convenience' of stopping at the market), and many personal services (e.g., house painting or movers - I want the reassurance from speaking to someone).
With regards to the higher education data line, school's out. Applicants won't get going again until the fall and admitted or returning students are working part-time/full-time jobs. They have all changed mindsets, released stress, relocated to Mom and Dad's, and otherwise abruptly changed their modus operandi. I'd look into whether this data line behaved similarly a year ago.
Posted by: Noah Cosby | June 15, 2007 9:01 AM | Permalink to Comment