8 Core Elements For Attribution Modeling Beyond The Last Click

Search marketers often benefit from the “last ad clicked” model because search is far down the purchase funnel. But limiting your analysis to just that is like operating with blinders on:  it doesn’t exactly give you the full picture of what’s happening. Instead, B2B marketers should perform attribution modeling across their marketing channels.

Today it is critical to look beyond the last click to find unexplored areas of opportunity. In fact, data from the various touch points in a sales cycle can be a veritable goldmine. Without tracking and analyzing multiple touch points, marketers can’t get a true ROI of their marketing dollars. As a result, they might not be fully optimizing their marketing initiatives.

Findings from a recent Forrester/iProspect study demonstrate the importance of attribution modeling by quantifying the symbiotic relationship that exists between display and search. 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 modeling can help you uncover.

By acting on the findings attribution modeling reveals, marketers can actually gain a competitive advantage, particularly during this economic downturn. Now is the ideal time to discover new opportunities and take advantage of current CPMs and CPCs before your competitors do. After all, the minimum costs will likely increase once more marketers uncover opportunities from their own attribution modeling.

But developing an attribution model for multiple channels can be a daunting task. When devising yours, consider the following core elements:

1. Technical resources – The availability (or lack thereof) of technical resources will help you determine how many channels to initially consider in your attribution modeling efforts. Assuming you don’t have an abundance of resources, start simple with just two channels to get a case study. Then leverage it to get the additional resources you need for modeling across more channels.




2. Attribution plan – Once you’ve decided which channels to include in your modeling, you should consider attribution between different products as well (i.e., a consumer clicks on an ad for Product A and then later converts on Product B). In addition, if your company houses several brands, the same scenario would be applicable to multiple brands.




3. Tracking – For each channel you’re measuring in your attribution model, you’ll need to have the same tracking system. Keep in mind that if one of your channels is display, you’ll want a tracking system that can track view-based conversions and not just click-based conversions. Should you decide to change tracking providers, don’t forget to keep a record of the historical data.




4. Cookie expiration – Set your cookie expiration to whatever your company accepts as an appropriate length of time for the sales cycle. If you’re unsure, it’s best to err on the higher end because you can always filter the data based on the time from the initial impression or click to the conversion.




5. Data cleaning – Set-up business rules ahead of time for data that’s not appropriate to analyze.  For example, if 97 percent of your data reveals that there are between 1 and 12 touch points during the life of the cookie, there’s going to be some cut off point above 12 touch points where it makes sense to scrub that data. Additionally, if you’re a global company, you may want to convert any spend amounts into one currency since many engines report in local currencies.




6. CRM data – After cleaning your data, it will be incredibly useful to marry your internal CRM data with your engine and conversion data. This will allow you to determine which purchase paths lead to the most desirable customer, and which lead to the least desirable. This will play into your optimization strategy.




7. Data weighting – There are a few ways to allocate success across different marketing channels. Probably the easiest method is to weight each channel equally, but you also have the option of taking the frequency of each channel’s exposure into account, as well as the placement of each in the purchase path (first, last, or middle touch point).
   

   For example, if someone has been exposed to a display ad five times in a seven touch-point path, then the credit given to display can be weighted higher. Or if display was the first touch point, you could make the case that this channel introduced someone to the brand and should be given more credit than the other channels. In addition, it would make sense to weight the data points based on whether they result in new customers or existing customers.




8. Reporting – There are an infinite number of report types, but certain ones are critical in attribution reporting. For example, you need to be able to see the purchase path (marketing channel, engine, or site, and keyword if applicable) by custom date range. In addition, you need to be able to see which channels (and within each channel, which engines, sites, or keywords) play the role of introducing new customers to the brand, which influence, and which net the transaction. And again, viewing this data by customer type (CRM data) will paint a more complete picture when attempting to improve overall results.

Overall, attribution modeling can help you find unexplored areas of opportunity. Marketers who capitalize on all it offers could boost their ROI, and possibly even gain a competitive advantage. Those who fail to tap into it will squander any advantage it might have provided.