For every conversion, there are a number of touchpoints your customers have the opportunity to be exposed to, leading them to the final purchase.
A touchpoint signifies any interaction with your brand a potential customer has, such as TV ads, social media, search engines, newspaper ads, and newsletters.
Touchpoints can be active or passive. Active involves a brand targeting their audience through marketing, like social media campaigns. Passive, however, could involve a customer using a search engine to end up on your brand’s website.
And with a steady stream of new marketing channels appearing, both online and off, it’s more crucial than ever for brands to know where their customers come from, and how they arrive at that final stage of the sales funnel.
This is where marketing attribution comes into play.
Marketing attribution is the science of identifying what touchpoints are driving purchases, and assigning a value to each.
This is a process that begins and ends with consumer data.
Using marketing attribution to identify your strong points.
How likely is it that a customer organically reaches your brand’s site and makes a purchase on their first visit? For most, it’s not likely at all.
The average consumer will get to know a brand over time, interacting with multiple channels and actively gathering information and getting familiar before purchasing.
With robust consumer data, brands now have access to all the knowledge they need to get an accurate picture of how their customers discover and interact with their brand.
Our latest research reveals:
- 36% use social networks to find more information about a brand.
- 51% research brands via search engines.
- 25% read an email or newsletter from a brand in the last month.
- 53% visited a brand’s website in the last month.
Using insight to assess the value of the different channels that lead to a purchase is how you know what you’re doing is driving a solid ROI, and your brand’s engaging customers where and when it needs to.
Identifying the perfect model for your brand.
There are multiple marketing attribution models, and rather than attempting a one-size-fits-all solution, each business needs to determine what approach is the one for them.
The traditional single-source attribution models are:
This model allocates the credit and revenue to the touchpoint that first put the customer in contact with the brand, regardless of whether a purchase was made directly after this engagement.
Example: If a customer initially comes to your website via a search engine and continues to engage with your other channels before making a purchase, the purchase is 100% attributed to organic search.
Here, the final touchpoint before a sale receives the entire credit for the conversion. It doesn’t take into account any of the previous interactions the customer may have had with your brand, such as website visits or newsletter clicks.
Example: A customer discovers your website via a Google search, then likes your Facebook page. Weeks later, they click through a Facebook post and complete a purchase. The sale is 100% attributed to social.
With the arrival of new marketing channels and increasingly diverse consumer journeys making these approaches insufficient, single-source attribution models are rapidly becoming obsolete.
Enter multi-source attribution.
Tailoring your attribution to create a truthful picture of the path to purchase.
In these newer, more accurate models, each touchpoint receives credit for the final sale or conversion. These are some of the most common multi-source attribution models.
The linear model gives the same amount of credit to each step of the consumer journey, indicating that every interaction the customer has had with your brand equally influenced their decision to purchase.
Example: A customer discovers your brand in a newspaper ad, likes one of your tweets, and visits your website before making a purchase. Each of these channels receives a third of the attribution for the revenue or conversion.
The positional model acknowledges the superior importance of the first and last interactions your customer has with the brand before converting. It integrates first- and last-click attribution, and additionally gives smaller credit to any interactions in between.
Example: Your customer discovers your brand via a search engine (first click), visits your Facebook page, and reads a newsletter (last click) before making a purchase. The search engine and newsletter interactions get X percent of the attribution, while the Facebook page interaction receives a smaller chunk of the credit as it’s deemed less important.
The time decay approach theorizes that the closer to the final purchase it is, the more important a touchpoint is and the more it influenced the purchase.
Example: A customer discovers your website via a Google search, likes your Facebook page, and downloads a whitepaper from your website before making a purchase or converting. The whitepaper receives most of the credit, followed by social and, finally, organic search.
The U-shaped model is pretty straightforward – it assigns 40% of the credit to the first click, 40% to the last click, and divides the remaining 20% to the touchpoints that occurred in between.
Example: A customer discovers your brand via a Google search, likes one of your tweets, downloads a whitepaper, and visits your website before making a purchase. Organic search receives 40% of the credit as the first click, social and content receive 10% each, splitting the leftover 20% equally, and organic traffic receives 40% as the last click.
For brands who want a more tailored approach, a custom attribution model is perfect. This allows you to create a personalized model, incorporating aspects of the existing models that are beneficial for your consumer journey and product map.
Using data to identify touchpoints and implement an attribution model.
So how do you identify the approach that suits you best and introduce an attribution model that works for your business?
Deep customer insight is crucial for not only the implementation of an effective model, but the continuous analysis of your individual consumer journeys and paths to conversion.
Using granular data to map your consumers’ attitudes and behaviors, you can be confident you have a true view of how they interact with your brand.
With this level of visibility, you can not only find a model that fits, you can optimize your marketing across the moments that really matter.