Leveraging Predictive Analytics for Campaign Attribution
As people continue to engage on a variety of devices, platforms, and channels, as well as through online and offline destinations, knowing when, where, and how to reach your ideal customer has never been more difficult. With consumers seeing between 4k-10k ads a day, it’s increasingly challenging to understand the channels, programs, and media destinations that drove a customer to take interest in your brand.
What is campaign attribution?
Campaign attribution is defined as the act of measuring and evaluating all the touchpoints that reached the customer throughout the customer journey. The goal is to determine which touchpoints, messages, channels, devices, ads, etc., had the greatest impact on customers’ decisions. That includes everything from the initial consideration phase to purchase and ongoing loyalty.
Why is campaign attribution important?
Over the past 5 years, leading analysts have said that adding four or more channels to an integrated campaign will increase results by 300%. As brands add more channels to reach their buyers, measurement becomes more and more complicated.
Furthermore, with the expansion of digital media and the convergence of spaces, ideas and shared experiences, brands today struggle to understand the right marketing mix. It’s hard to make all these channels work together to drive sales. A better understanding of the marketing mix, along with the customer journey, allows brands to better allocate resources, ad budgets and messages to align within spaces that best reach their target audience.
Seventy-one percent of B2C marketing execs say that demonstrating the value of marketing to business leaders will be very — or extremely — challenging during the upcoming year. Attribution will take center stage as CMOs present success stories to the C-suite, the board, and shareholders.
Types of Attribution
Marketers use a variety of approaches to attribution today. In many cases, these attribution types build upon themselves to provide a fuller picture of the purchasing journey and of how customers interact and engage with a brand.
- First-Touch Attribution: Usually described as “first-click” or “first-interaction.” This type of attribution model assigns 100% of the credit for each conversion to the first interaction a prospect had with your brand.
- Last-Touch Attribution: On the flip side, last-touch attribution assigns 100% of the credit for each conversion to the last interaction a prospect had with your brand.
- Last Non-Direct Attribution: For many brands with short buying cycles or high repeat purchases, last non-direct attribution is a key attribution methodology employed to help determine conversion events. This attribution model assigns no weight or credit to direct website or bookmarked URL traffic. All attribution is assigned to the channel, ad, or experience leading up to the direct-traffic event.
These types of attribution models are very straightforward. They can work very well for smaller advertisers who leverage three or fewer media channels.
However, as a company grows, more advanced attribution models can do a better job of factoring in all the touchpoints a consumer or business buyer may have with your brand. This approach is called multi-touch attribution. There are five common multi-touch attribution models:
- Linear Attribution: Linear attribution gives equal weight and revenue credit to all touchpoints throughout the buyer journey.
- Time-Decay Attribution: The time decay method attributes more credit to the most recent marketing touchpoints over those earlier in the process. This method is most commonly used by B2B brands.
- U-Shaped Attribution (position-based attribution): U-shaped models typically attribute 40% percent to the first touchpoint and 40% to the last touchpoint prior to the business transaction. The remaining 20% is divided among any touches that happened in the middle of the journey.
- W-Shaped Attribution: This method is similar to U-shaped attribution, except W-shaped attribution attributes credit to the creation of a sales opportunity. All three major touchpoints (first touch, lead creation, opportunity creation) receive 30% of the credit, with all other touches receiving 10% credit.
- Full-Path Attribution: Full-path attribution builds on the W-shaped model to include the final close of a sale. This type of attribution is most helpful when dealing with complex and lengthy sales cycles.
How does predictive analytics support campaign attribution?
In theory, data-driven of attribution provides the most reliable measurement, as it takes a holistic view of the buyer journey and gives credit to each and every touch point along the way. This type of modeling also provides the most insight what media platforms, channels, devices, etc., you should incorporate into your marketing strategy to drive needed outcomes for your business.
Driven from the highly fragmented media space and the proliferation of devices the need for more advanced measurement solutions is needed to understand all the activity that lead up to a conversion event.
To that degree it is becoming not only harder for marketers to engage with customers, but to reach new prospects. With the help of machine learning, brands can test new platforms and be confident of driving outcomes earlier in the test with predictive analytics.
With predictive analytics as part of your attribution strategy your marketing campaigns become more action oriented. Predictive analytics allows marketers to optimize on a predictive value vs. looking at historical result. So no matter what attribution framework your organization is working with, incorporating predictive analytics into the fold will make your results much better.