The customer journey, also known as the path to purchase, is divided into three phases: awareness, consideration, and decision. The length of the consumer journey is growing and is not a straightforward or a short journey. Just to turn a user into a customer requires the three above phases. The number of touchpoints at each of those phases could be in the tens or even hundreds. With so much data available, it can be challenging for marketers to accurately determine what is and isn’t working.
Marketers might be able to count the leads they’re producing, but how can they precisely identify the marketing channel from which they came? Even worse, how can they credit their marketing for closed income if a lead turns into a sale? Making clear linkages between sales and marketing can be challenging when there are so many channels at play.
The last-click attribution model is the one that many ad platforms choose, which means that all the credit goes to the channels that were used last.
This isn’t a reasonable attribution model to employ considering how many touchpoints are needed to lead users along the road to buy. The influence of everything else is ignored by last click, even though it might be a great model type to understand how channels are closing revenues to purchase. Nevertheless, this is the most common attribution model used across industries and the one that Google uses in Universal Analytics.
Why Return on Advertising spend (ROAS) matters?
Return on Advertising spend (ROAS), as a definition, is a marketing metric that measures the efficacy of an advertising campaign. ROAS helps businesses evaluate which methods are working and how they can improve future advertising efforts.
ROAS is crucial for quantitatively assessing the effectiveness of advertising campaigns and how they affect a store’s bottom line. Insights from ROAS across all campaigns guide future spending, strategy, and overall marketing direction when combined with client lifetime value. Ecommerce businesses may decide where to invest their advertising budgets and how to increase efficiency by keeping a close eye on ROAS.
The ROAS formula may be summarized as follows:
Although as an equation it seems relatively straight forward, the challenging part is whether Marketers should calculate ROAS by Direct only or by Direct and Indirect conversion revenues.
Direct we call the revenues of promoted products that have been attributed to the running promotional activations, while Indirect we call the revenues of promoted products, that have not been attributed, but could potentially have been influenced by the promotional activations running. For simplification reasons this is what we will call from now on, Direct & Indirect Impact, in the rest of the post. Read more and uncover our take in this.
4 Hypothetical Cases of a Customer Journey
Imagine you have placed a banner within an online store, and you want to measure the Marketing impact of it. How do you measure it? Let’s assume we have 4 different hypothetical cases of a customer:
It is the most straightforward case. Yes, the visitor saw or clicked the banner and completed the purchase of the product that was advertised on the banner. Naturally the attribution should go to the banner advertised and should be counted in the Direct Impact of the Banner.
The visitor saw or clicked the banner, had another action after, for instance navigated through the menu or he read the reviews of the products within the website, or read a blog post and then went on and purchased the product advertised on the banner. In this case the last attribution model does not consider as last interaction the product banner, although it may have been what influenced and convinced the consumer to make the move and purchase the relevant product. This means that the banner seems less effective than what is, since it does not report all the sales attributed to it. In this case the banner gets in the final equation, but this time as an Indirect Impact since it was not the last user interaction.
The visitor saw and clicked the banner but went on and purchased another product from the same company. E.g., a banner of a L’Oréal face cream, led to the purchase of a L’Oréal sunscreen. From a broader point of view, the banner influenced the consumer to take a certain course of action, and therefore ad platforms credit the revenues of the other product to the banner. But the marketer should know what the impact on the precise promoted products is, and not on irrelevant products. The right attribution model should show how many face creams were purchased in case the banner had a face cream on it.
A purchase of a product for sure is a multi-factor decision and understanding the psychology of the consumer is the key for decoding purchasing patterns. Market conditions, different Company Marketing initiatives, and Competitive Activities all have an impact to the consumer’s behavior.
Recent research conducted by Melbourne Business School, even found that “When a pair of competitive brands advertise intensively and simultaneously, sales for both brands are increased”. This is a proof that marketing activities should not work independently of one another, or as if they do not belong in a whole ecosystem of different dynamics. But still Marketing Impact, whether it is Direct or Indirect, should give a clear visibility of where you stand on the precise product advertised, that advanced analytical techniques could help you with.
The eshop visitor did not engage with the advertising banner but regardless of that, purchased the relevant product. This is a transaction that should get included in the calculations of the Marketing Manager, since it indirectly increases sales of the product advertised. The user might have just seen it, without clicking and moved directly to the checkout process, or it could just have been a loyal customer that went on and bought the product right away.
All in all, Case 1 is an example of Direct Marketing Impact, Cases 2 and 4 of Indirect Impact and Case 3 has no visible impact. Therefore Cases 1, 2 and 4 are the ones that should be measured in the ROAS, helping Marketers understand if the campaign was money well spent or not.
But what if you had in the tip of your hands all the information available, regarding Direct and Indirect Marketing Impact? Now with the right tools you can!
Case studies ran from Convert Group
We examined the metrics from a random sample of a dozen distinct campaigns from popular European brands, as they were reported through the Internal Promotions report of Google Analytics, a widely used platform for tracking the campaign performance of site banners. By analyzing the products of every single transaction that was attributed to a specific campaign, we found that the majority of those (from 60% up to 90%) did not contain promoted products. Moreover, half of those misattributed transactions did not even contain a single product from the brand that was promoted. In addition, the reported revenues were considering the total value of transactions, and not only the revenues of products that participated in the campaign.
This is further evidence that brand companies, that promote their products in a retailer’s website, cannot rely on simple attribution models and need to have data granularity at the SKU level to calculate an accurate ROAS for their campaigns.
With convert Group’s platform you can monitor the sales directly and indirectly impacted from the Marketing activations on the retailers. What’s more? You can do that in real time, for small or big activations running.
In other words, brands can get:
- The exposure of their promotion on retailer’ pages
- The engagement of total pages including the promoted products
- Exact banner views and user interactions, making it easier to calculate CTR
- Conversions for both Directly & Indirectly impacted orders
- Precise outcome in value
- Total activation’s ROAS for both directly & indirectly impacted orders, one of the most important activations KPIs
Given that there might be more targets for a campaign, other than ROAS per se, for an activation to be considered impactful, the brand needs to know its market share in sales value compared to specifically defined targets set for a particular campaign. At the same time for maximizing activations results, there is a monitoring of the brand’s sales value evolution vs the rest of the category, of the competition benchmark for the whole duration of the campaign and of course there is a drill downed analysis on an SKU level for the products affected by the activation.
But our offering doesn’t stop here, as we constantly work on measuring revenue incrementality through AI-algorithms, advanced data enhancements and supporting new activation types.
To learn more, book a demo with one of our eCommerce experts.