Commentary

4 Things You Should Never Do to Measure Digital Marketing Success

Calculating attribution is one of the most challenging tasks of modern marketing. Although we have access to more data than ever before, coming up with a plan to accurately measure which marketing tactics are generating the most results is a lot of pressure. How do you make sure you’re getting it right? 

There’s a lot of information about what you should do when adopting new attribution models, but sometimes it’s what you don’t do that affects your outcome the most. To help you successfully launch a more accurate way of measuring attribution, check out these five don’ts.

1. Don’t rely on last-click or first-click.

For many years, marketers have relied on clicks as an indication of digital marketing success and assigned full credit to either the last asset or the first asset someone clicked before converting. The problem with relying on last-click or first-click attribution is it discounts everything in between.

advertisement

advertisement

Think about the last time you purchased something online. You likely saw an ad, Googled the item, read reviews on a third-party site, watched a product video, shopped around to see if you could find a better price, and then finally bought the item.

Your path to purchase is rarely linear, and the same holds true for the buyers you want to convert. If you’re still using first-click or last-click attribution, consider switching to a more sophisticated model that factors in all engagements leading up to a conversion. 

2. Don’t be afraid to dive in to the data.

In my experience, the No. 1 reason marketers haven’t launched a new attribution model isn’t because they don’t believe it’s worthwhile: it’s because they’re afraid they’ll mess something up. In many cases, when we see data presented in a new way, we start to panic, but you have to start somewhere. 

Begin by analyzing one new client’s purchase path. Get granular by identifying every marketing and sales touch with the client and mapping out the full buying cycle. A single example can teach you a lot about your clients’ purchase path and your organization’s sales cycle.

3. Don’t change your methods too often.

When you launch a new attribution model, consistency is key. Pick a model, pick a time frame (i.e., 30, 60, or 90 days) and go for it. Do it for a couple of quarters, and then reassess. If you can’t decide which model makes the most sense for your organization, start with the even-weighted model where each touchpoint is assigned equal value. This way, you can factor in every event that influenced a customer to make a purchase. 

4. Don’t use marketing jargon to explain results to business leaders.

Even well-aligned marketing and sales teams often speak different languages when it comes to measuring success, which can lead to frustration when you’re attempting to present results to business leaders. While you might be excited to discuss your new marketing assets and the audience engagement metrics like video views or landing page conversion rates, you might be getting a little deeper in the weeds than your executives want to be.

So instead of sharing engagement metrics, focus on how your efforts are impacting the bottom line by shortening the sales cycle, increasing deal size, or expanding the number of contacts within an account. A more advanced attribution model can you help you draw these conclusions.

6 comments about "4 Things You Should Never Do to Measure Digital Marketing Success".
Check to receive email when comments are posted.
  1. Alex Hultgren from Quantum Storey, July 17, 2018 at 1:35 p.m.

    Hey Drew, great article - thanks.  One thing to consider:  I've been watching the development of attribution models for a long time, and the biggest barrier I've seen in implementing new models - particular when working for larger companies - is when there is so much advertising investment in broad reach media (broadcast TV, terrestrial radio, OOH).

    Although some people I’ve spoken with in the industry are getting pretty slick at developing models to determine the probability of someone’s exposure to, say, a digital billboard (based on mobile location data and/or known commuter routes), the Achilles heel in true attribution modeling remains in trying to tie that very inexact ad exposure back into a model with the precision of digital measurement. 

    But in terms of pure digital exposure, you are spot on.  We should be keeping track of the sequence of every message, on every site, in every format, and map it out to optimize accordingly.

  2. Gabriel Hughes from Metageni, July 18, 2018 at 8:29 a.m.

    To Alex's point, it is possible to combine multi-click attribution with impression related attribution and also above the line. The answer has to be to revert to market mix modelling and then use digital attribution to get more granular within the digital channels. The challenge is that you have to combine different methods in order to address differences in the data sources and how they are measured, which means you also need to figure out to interpret different models. Less precise data means less precise results, but what else can you do?

    So I suggest a hybrid approach. The only alternatives to a combined/ hybrid approach is either (1) abandon the granular digital data, or (2) leave out these important influencer/ branding challenges: neither is really acceptable. 

  3. Ginna Hall from Nielsen Visual IQ, July 18, 2018 at 3:43 p.m.

    This is spot on! Some of your readers might find this post helpful. It's a quick read on the difference between various attribution models: https://www.visualiq.com/about/blog/multi-touch-attribution-guide

  4. Drew Sollberger from Spiceworks replied, July 19, 2018 at 11:36 a.m.

    Great points, Gabriel and Alex! I absolutely agree that different models can be needed for different investments, and in fact, I've found it valuable to look at the same programs and data through multiple models to see what trends stand out and use that to further refine modeling. 

  5. Jeffrey Keenan from Leadsrx, July 20, 2018 at 11:52 a.m.

    Great article!  We (https://leadsrx.com) completely agree with the 4 points you have made.  It's very easy to get overwhlemed when taking on new ways to measure advertisments.  We always suggest 6 weeks of data should be statiscally significant to make your first changes to spend, channels etc.  Multi-touch attribution is essential for both B2B/B2C and even Radio and TV.  Once again great article and it's great to see attribution becoming so prevalent as of late.

  6. Drew Sollberger from Spiceworks replied, July 20, 2018 at 12:08 p.m.

    Thanks for the feedback, Jeffrey! Agreed, it's great to see attribution being approached more directly these days!

Next story loading loading..

Discover Our Publications