2. In advertising, an attribution model will allow marketers to
look at the team of ads that contribute to a sale or
conversion over an extended period of time. So instead of
the traditional method of crediting a sale or conversion to
the last ad clicked or viewed, an attribution model will
attribute credit to each ad or “touch point” within the sales
funnel.
The goal behind attribution modelling is to obtain a full
picture of what is happening along each marketing channel
and to understand the degree of influence each ad has on a
consumers’ decision. By using an attribution model to
track and analyze multiple touch points, marketers can gain
new insights, optimize campaigns, and get a more accurate
reading on ROI.
3.
4. An article published in 2009 by Search Engine
“Findings from a recent Forrester/IProspect study.
The study shows that 27 percent of internet users initially
respond to display ads by conducting a search on the
company, product, or service mentioned in the ad. In
addition, that figure jumps to 49 percent when latency is
taken into account. This data clearly highlights the need
to consider display’s value in driving people to search.
This is exactly the type of opportunity attribution
modelling can help you uncover.”
5. The biggest challenge to setting up an attribution
model is identifying how much credit to assign
each attribution. In other words, a marketer must
determine how much influence to assign each
touch point or ad. Does the initial ad get most of
the credit or was it the third ad in the sales funnel
that was most influential? This can prove
extremely difficult when we consider that there
are many other contributing factors, such as the
timing of the ad, decay rate of the ad, what
products were sold, the amount spent, etc.
6. A good attribution model should also
account for the factor of uncertainty. Was the
buyer recommended by a friend? Did they
see the product in a magazine ad or on a TV
commercial?
In order to ensure accuracy in the credit
attributed to each ad, analysts must
continually test and re-calibrate attribution
models for extended periods of time. Only
then will they have successful models that
will allow them to make effective marketing
decisions.
