There is no denying it: the success of any digital campaign depends directly on the metrics used to evaluate the results based on the objectives outlined. The good news is that, in the digital environment, virtually everything is measurable. But among the variety of models available, which would be more appropriate: measure by the first click, the last, both, the number of views..?
The online consumer is in contact with several channels simultaneously, which doesn’t make our work easier. Being truly omnichannel implies a higher degree of commitment to channel consistency and tracking the purchase process, including the qualification of leads.
First of all, let’s talk about some attribution models:
The last touchpoint
As the name itself suggests, this template assigns the conversion to the last campaign or point of contact of the lead with the brand. It is widely used in analytical tools such as Adwords and simple enough for those who are managing only two campaigns, for example. In the case of multiple campaigns, however, the last touch model can be treacherous when it comes to measuring the ROI of each campaign on different channels.
Okay, the customer placed an order. But how do you know exactly which of the campaigns impacted them before the purchase? If the conversion took place in e-commerce, that’s somewhat easier. But what if they bought it in the physical store? What if they opened an email marketing but clicked on the Adwords campaign? We’ll not even get into the merits of social media. Besides, while a huge number of users view display campaigns, only 16% click on it.
Still about interaction: how can we evaluate the impact of organic search on the customer that seeks the best price? We, marketers, need to measure the effectiveness of each strategy to intelligently allocate resources in future campaigns, and last touch attribution clearly doesn’t tell the whole story.
This alternative incorporates multiple campaigns and touch points, including visualizations and clicks on ads that preceded the purchase. The ideal course of action would be to test different models of multi-touch attribution to customize the most adequate model to the company’s marketing goals, checking which campaigns are influencing the purchase decision.
This approach makes it is possible to assertively analyze how advertising is impacting the online audience. So setting the budget for each point of contact becomes a much simpler task.
Measure to attribute
You can not manage what you’re not measuring. From the data provided by email marketing campaigns, for example, we can measure single opening, clicks and conversion rates. But what happens when the customer likes a product featured in the email, does not click, but goes directly to the physical store? These are situations that make marketers awake at night.
On the other hand, if only a few people actually click on ads, are they contributing to the conversion? The answer to this question lies in the A/B tests. By looking at how many visitors viewed an ad compared to a second version, we can measure the effectiveness of the display strategy and track how many percents of visitors closed the deal after contact with that type of campaign. Thus, the chances of assertively assessing the impact of the campaign and better allocate the budget only tend to grow.
Creating your own attribution model may seem hard and time-consuming, but keep in mind that there are many metrics options available and it’s up to you to select the ones that are the most relevant to your business. The key is to create from an existing model and adapt it to your unique needs, the number of active campaigns, channel diversity, and brand touchpoints. Track the conversion process closely to make the necessary changes and refine the process as your business evolves.
Also, count on a strategic partner like Pmweb to support you on this journey.
Source: Shop.org and Econsultancy