31 Jul 08 Are offer impressions the marketer’s Higgs particle?

Humanity is currently engaged in a search for the most fundamental particle of physics, the Higgs Boson - and marketers should be seeking the analytics equivalent, the impression (achieved when attention meets information). However, it seems many people are still stuck at an atomic level of analytics, or worse.

Why are offer impressions a better metric than a catalogue page view?

 

Offer Impressions are a better metric than a catalogue page view for many reasons that can best be appreciated when looking at the short history of the web. Initially, the metric that was used as common currency for doing apples to apples comparisons of web real estate was the “hit” – the number of client requests to a web server. This was quickly outdated as pages became more sophisticated and “hits” were being registered when every asynchronous element refreshed (widgets etc), tracking servers were called and a myriad of other activities resulting in “hits” took place.

 

Then, to replace this came the Page View metric. Marketers decided to disregard how many “hits” there were since it was no longer one page = one “hit” and it was more valid to see how many page views there were. However, this metric soon became outdated as well when AJAX (asynchronous JavaScript and XML) became the standard for usability in the Web 2.0 world. Now, more than half of a page’s content could change without a new “Page View” ever being registered since the URL remained the same.

 

So, the impression was born to be the apples to apples comparison metric for marketers. Regardless of what all of the information on a page was doing, how many servers where “talking” to produce a complete page of information, the one thing that would remain constant and relevant to marketers across all mediums was – how many times did my offer appear in front on the eyeballs of a consumer.

 

Catalogue Page view’s suffer the same drawbacks as page views with regard to performing accurate analysis for a marketers spend – despite being the common currency in the analogue world where “offer impression” granularity is hard to come by since offers per page vary from page to page. However, ad space inside catalogues is still sold at the offer level, indicating that more granular metric is the more relevant one to marketers.

 

We can track catalogue page views, yet, if this is all that is looked at, then the offer impressions that appear in search, and not on a catalogue page view is never counted, despite this being the more relevant and targeted advertisement. Some may think you could just measure both and report this, but now you are dividing what would otherwise be a consistent metric, making it harder to understand and do accurate analysis on. What is the point of looking at a report that may say

 

100 Catalogue Page Views

13 Search Listings

813 Offer Impressions

 

Rather than

 

813 Offer Impressions

13 Search listings

 

Where catalogue pages are evident inside the more granular metric?

 

The result of this approach is that when comparing to other media and you are looking at

 

Print:                                     Circulation

Print:                                     Readership

Print/ catalogues:            Distribution

Viewership:                        TV

Listenership:                      Radio

Visits:                                    Web

 

You have one universal metric to apply to your ROI calculations.

 

 NB: This will become much more important when we look forward to a more convergent Internet as described here by Kevin Kelly.

 

 

 

 

 

 

Part 2. Using a universal metric when calculating ROI? The offer Impression

 

Reducing offline media to a universal metric – the offer impression, is fairly intuitive, but has some intricacies in finding the correct estimates for certain variables.

 

Offer Impressions = (Circulation x (wastage factor)) x (probability of reaching ad page depth) x Offers per page

Offer Impressions = (Readership x (wastage factor)) x (probability of reaching ad page depth) x Offers per page

Offer Impressions = (Distribution x (wastage factor)) x (offer impressions per person)

Offer Impressions = (Viewership x (wastage factor)) x (offer impressions in TVC)

Offer Impressions = (Listenership x (wastage factor)) x (offers in radio commercial)

Offer Impressions = Offer Impressions

 

Now you have an apples to apples metric to begin calculating ROI (In fact, you could even work out offer impressions per unique visitor – however, this is a different yardstick compared to the other media that are largely absent of any tracking).

 

The next thing required is to establish the quality of an offer impression in each medium with respect to sales. This is the responsibility of the marketer, not the ad network. The job of the ad network is to generate the highest quality offer impressions in the greatest quantity possible for the lowest possible price.

 

The general formula then for establishing media effectiveness would look something like

 

Media Effectiveness = Sales per offer impression = Sales / Offer Impressions

I.e.         Sales = Offer Impressions x Media Effectiveness

 

This can now be ascertained per media channel.

 

ROI = Sales/ Dollars Invested

 

 

Hence, your ROI can be predicted and measured by

 

ROI = (Media Effectiveness x Offer Impressions)/ Dollars Invested

 

Now, to get a relevant statistic for this you really need to run a control set of offers, probably simultaneously across different media that is unique to each state – eg Radio in Melbourne, Search in NSW, TV in Queensland, and then assess what the performance was in each medium so that you can ascertain what the Media Effectiveness was for each channel. If you have eCommerce enabled, you can get an idea of the effectiveness of online channels by seeing the quality of different traffic streams on online sales. However, this totally ignores web to store conversion which research has indicated counts for up to 95% of online traffic on the eCommerce enabled sites.