Saturday, May 15, 2010

Email Analytics: Part 1 - Costs of an Email Marketing Campaign

From all executives:
"The least costly campaign to setup is an email marketing campaign - Only costs involved is to have an agency setup a few creatives and mail them out from the company to the list of customers!!!"
How often have we heard this?

Sending the campaigns in the above way would be "extremely costly" in the long run because:
(1) Frequent mailers would cause these to be spam thus missing out on potential buyers - Folks will BEGIN to IGNORE good offers
(2) Create a wrong brand image of the company
(3) Habituate buyers to something like a 10% discount - He will not buy without htat
(4) Result in high bounce rates if the campaigns and the landing page tell different stories

For an effective email campaign, the drivers would be the following:
(1) Analytical Model to score your Email opt-in list using mining techniques - SELECTION ANALYTICS COST
Engage a firm that employs Data Mining techniques like Logistic Regression (LR) to score your email list based on factors such as:
a) Past response to emails, offers, discounts, messaging etc
b) Browse/buy Behavior on the site in the past
c) Factors involved in prior purchase: marcom source, product bought, ....; Lifecycle analysis to predict who is likely to respond (e.g: Printer buyer who is running out of ink!!)
d) Integration of demographic and other factors data from 3rd party sites like BIS
e) Other

(2) Email Design Testing & Landing Page Optimization for the campaign (A/B, Multi-variate Testing) - TESTING COST
Next Step is to be clear about the intent of the email campaign.
What are we trying to do?
a) Sell a deal (like 10% off or $100 off or....)
b) Communicate hot new products arrivals
c) Use prior information that a customer needs a certain product
d) Other
And to design landing pages for the email visits. Landing page is the page where these email visits are going to land on your site.
So if they see a link xxx on the email the xxx click leads to the landing page on your site.

The landing page link xxx is very critical because if it communicates a different story from the email, the results would be devastating

Suppose you have identified 10,000 folks to send the email out to, don't send them rightaway
First identify a bucket say 500.
Say you have 2 recipes of the landing page for the campaign.
Send half of them to link xxx1 and half to link xxx2.
Measure success and the statistical confidence. If not high, increase the 500 bucket
Once you know which recipe is better, use that for the actual campaign

(3) Create the email creatives & Landing Pages - CREATIVE CREATION COST
This is a subset that comes between (1) and (2)
It is important that the intent of the campaign is properly understood when the email creatives and landing pages are designed
And that there are 2-3 versions to test

(4) Measure the ROI of the campaign and store the results for future learnings - POSTMORTEM ANALYTICS COST
This is a stage often ignored.
You could have an organization that has sent out a million email campaigns without learning anything

So total cost is SELECTION ANALYTICS COST + TESTING COST + CREATIVE CREATION COST + POSTMORTEM ANALYTICS COST.

Will have a series of posts on this topics in the coming days

Friday, May 7, 2010

Interaction between paid & unattributed traffic



You have a paid marcom campaign - you take it off - and suddenly you find a drop in unattributed traffic.

Let us take a hypothetical scenario.
Weekly traffic dropped 40% as a result of taking out a campaign that generated approximately 10,000 visits a week. The expected fall was 25%, but there is an extra 15% fall due to drop in unattributed/direct load traffic. You are perplexed :O
What caused this?

This can be graphically represented as a bridge chart:






In this post, let us go through a workflow of how to mine this information and communicate this to business stakeholders
(After all presentation is an art - if you can't present your idea through, it will never get implemented)

STEPS TO FOLLOW/DRILLDOWN THE PROBLEM
Here I would say are the steps to follow before we decide to take out a campaign

I) Capture the first time and repeat visits that resulted from the ODG Campaign for the last few days (maximum of 90 days)
Calculate the Revenue per visit separately for each
II) Arrive at a statement:
"Campaign C results in an average of x visits a week landing from a campaign and y visits that did not land on the campaign on the same visit but on a prior visit"
III) Revenue Impact of removing the campaign would be
x*px + y*py where px and py are the average RPV for the x and y visits

Now let us go through an actual workflow of analyzing this information:

DETAILED ANALYSIS
Step I:
Job to be done: Capture the visits that resulted from the ODG Campaign for the last few days
Method: Create a visit segment with a condition on traffic source as from campaign


Get the visits for above segment - it is x.

Job to be done: Capture the visits wherein the user had not used the campaign on the same visit but on a prior visit
Method: Visitor Segment with condition on traffic source as from campaign and visit_sequence_number > 1


Get visits for above segment - it is w.
Then y = w-x i.e. visits that came to your site as direct load - but on a different visit had seen the campaign.




Step II:
Here is what we found:
"Campaign C results in an average of 10000 visits a week landing from a campaign and 6000 visits that did not land on the campaign on the same visit but on a prior visit. Their RPVs are $4 and $6 respectively."

So revenue impact of removing this campaign is
10000 * 4 + 6000 * 6 = 76000


This is just a directional workflow
So when you take out a campaign, bear in mind that you might be impacting direct traffic as well.