Direct marketers use Matchback Analytics to attribute sales to the activity that theoretically caused the purchase to happen. Matchbacks were originally designed to prove that catalog mailings were responsible for web sales. Now, matchbacks are well suited to measure influence.
Let's look at a few customer orders.
Order #1: Customer received catalog on November 1. Customer purchased online on November 10, using the keycode from the back of the catalog. This one is easy, the catalog gets credit for the order.
Order #2: Customer received catalog on November 1. Customer received marketing e-mails on November 3 and November 5. Customer purchased online on November 10, and did not use a keycode. The catalog brand would probably allocate this order to the catalog, ignoring any role that e-mail marketing played in the purchase.
Order #3: Customer received catalog on November 1. Customer received marketing e-mails on November 3 and November 5. Customer clicks through to the website from a paid search term on November 10, purchases online, and does not use a catalog keycode. Catalogers would like to allocate this order to the catalog, paid search mavens might want to allocate this order to paid search, e-mail marketers probably lose out in this instance.
Order #4: Customer received catalog on November 1. Customer clicks through to the website from a blog featuring merchandise offered in the catalog. Customer purchases online on November 10. Catalogers would immediately allocate this order to the catalog.
In the last three instances, the marketer "assumes" that one form of media drove the order, and creates business rules to proceed with allocation of sales. And, of course, in the last three instances, the catalog marketer makes incorrect assumptions. The assumptions are better than the assumptions made in 1999, but the assumptions are flat-out wrong.
When a catalog brand measures influence, there are two different allocations.
There is direct allocation, as illustrated above.
Then we have influence allocation.
In Order #2, the catalog gets credit (if that is how matchback business rules are written), while each e-mail campaign gets half-credit for influence.
In Order #3, the catalog gets credit, while two e-mail campaigns and paid search receive one-third credit for influence.
In Order #4, the catalog gets credit, while social media receives 100% influence credit.
Each quarter, we produce a table that illustrates, for each channel, direct attributed sales, and influenced sales.
|Direct Sales||Influenced Sales||Index|
|Other Online Marketing||$1,000,000||$1,000,000||1.00|
What you are likely to see is that emerging channels have a high "influence index". In other words, we don't attribute orders to the emerging channels --- we simply don't have business rules to do this, so we attribute orders to the most established channels. But if we focus on influenced sales, we notice that channels like e-mail and paid search and social media play a bigger role, helping cause an order to happen.
Influenced sales make a huge difference in viewing a "mutlichannel strategy". In the illustration above, e-mail, paid search and social media are key influencers. They do not get direct ROI attribution, but are clearly used by the customer as part of the purchase process. From a strategic standpoint, these channels should receive strategic attention. Or maybe catalog marketing should not receive direct credit for all orders!
Either way, the marketer views the world differently when focusing on both ROI and influenced orders.
A final note: In a perfect world, the marketer executes catalog and e-mail test/holdout groups, then measures influence in mailed/holdout groups, subtracting the differences to measure true ROI and true influence.