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Analytics to grow Digital Commerce and Improve Digital Marketing ROI

Written by Maavrus

January 11, 2023

marketing

Hi. Welcome to Expert Talks at Maavrus, in the previous video, we spoke about why business leaders and marketing teams will need to have a mindset shift in the way they look at the effectiveness of their marketing spends.

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That is because, in the current world, customers are exposed to a plethora of physical and digital touchpoints in quick succession. And so for any team to assess says the impact of a single campaign on a business or sales outcome is just next to impossible. In this video, we will speak of what could be a good marketing effectiveness measure and two what are some of the ways in which one can understand and attribute the impact and contribution of various campaigns and touchpoints to marketing performance. 

So a good marketing effectiveness measure will need to be aligned with the business goals and business goals typically depend on the life stage of that particular company. So is the company in the intro of the early stage, is it in a growth stage, is it in a maturity stage or is it a decline stage and so on. And hence the marketing measures for each of these particular stages will differ.


For a company in the maturity stage, I personally out of my experience with a marketing effectiveness measure called rolling return on marketing spend which is essentially the gross margin earned by the company during a predefined rolling period divided by the marketing spend by the company in that period.

So this typically ranges between four to 15 depending upon the industry and the maturity of the company. Now, this period for which this is taken typically depends upon the shopping cycle in that industry. So for a grocery retailer, the rolling period could be possibly ten to twelve weeks, for a fashion company it could be possibly five to six months, for a furniture retailer possibly twelve to 15 months, and so on. 

Secondly, this is a relative measure and not an absolute one. So you look at the rolling return on marketing spend and compare it with the same number for the previous periods to see if it is trending in the right direction. Also, the fact that we take gross margin into account corrects for any additional or lesser discounts that the company may have given during that particular period. 

Lastly, for a company that is in a very mature geography and at a mature stage, very mature stage, one could also normalize this measure based on incremental market share. So has the company lost or gained market share during the period? So for example, if the company has lost market share during the period it means that the marketing teams and campaigns will need to work that much harder to achieve the same level of success and so one needs to normalize that particular measure. 

So typically between business leaders and marketing teams, they pick one or at best two marketing effectiveness measures on which they are both aligned and that forms the basis on which future marketing performance is reviewed. So let us now discuss ways for attributing the impact of various touch points and channels on the overall marketing performance. In the last video, we spoke of three broad areas. 

The first one is the understanding impact of each individual touch point. So in the slide, you see that customers seem to be adopting multiple shopping journeys. The overall conversion during the period is around 50%. Now specifically in Customer journey C you see that the customer has not engaged with email at all and the conversion is around 10%.

So by calculating the way that I’ve shown the slide you could arrive at what is called as the removal effect of email, which essentially means that if you remove email from all marketing channels, what would be the impact? So this shows that if you remove email entirely then 80% of your conversions would get impacted. You could use the same approach to understand the removal effect for each of the other channels and then normalize it for a 100% total. You see that email has a 30% weightage, WhatsApp has a 19% weightage, and so on. 

The next area is understanding the impact of the sequence of touch points. This is important because different channels or touch points are likely to have a varying impact depending upon which step of the customer journey the customer is in. So in this image, you will see that YouTube and Snapchat seem to have a greater impact when the customer is in the awareness stage, whereas Facebook and Instagram seem to have a greater influence when the customer is in the action or the purchase phase. 

The third area is understanding the time decay impact. So once a campaign is done, the impactor mind share of that campaign tends to reduce in an exponential manner as time passes. Now this rate of loss of impact is different for different channels. You will see that possibly TV has a long time frame where the customer tends to recollect the campaign whereas Digital has a shorter time frame. 

So now that one has understood the importance of these three areas, one needs to see what are the approaches to get a comprehensive or holistic view. And that is where Attribution modeling approaches like Marco Chain or Shapely Value can be used. I’m not going to the specifics of those but it suffices to say that if you have good quality attributable data then these models can help the marketing teams to understand the impact and contribution of individual channels to the overall marketing effectiveness measure.

It can also help them understand how each of those channels and touchpoints is contributing to the marketing performance at each step of the customer shopping journey. So in summary, a marketing effectiveness measure needs to be aligned with the business goals which are typically dependent upon the life stage that the company is currently in.

Number two Attribution modeling is an internal metric or approach that the marketing team uses to see how it can continually fine-tune and maximize its marketing effectiveness Performance. 

Number three for attribution models to work, good quality and attributable data are required. Otherwise, garbage in is garbage out. 

Number four while all these models work on past data, the business environment and situations keep changing. So marketing teams have to constantly innovate and experiment with new ideas and create data that can then be continually fed into the models for them to get more recommendations which they can then try and scale. I hope you found this video useful. Please do follow us @maavrus.com. Thank you.

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