Use lean analytics to calculate your ROI correctly (Part 2)

Bill Su
Analytics for Humans
8 min readFeb 5, 2017

In the last piece of this series (linked here), we presented a lean analytics framework that can help businesses quickly calculate the return on investment (ROI) of each of their individual marketing channels. To recap, the framework is illustrated in the infographic below:

In this article, we are going to further expand on each of the steps in order to help you identify and collect metrics that will help you find the real ROI of each of your marketing channels.

Acquisition

Acquisition is the first step in all marketing processes. Every business has a target audience and acquisition describes the steps a business takes to make the target audience both aware of and engage with the company and its products/services.

The Acquisition phase can be broken down into awareness and engagement. Awareness describes impression, meaning that your target audience is cognizant of your products/services. After becoming aware of your business, it’s imperative that potential customers actively engage with your business, otherwise your marketing efforts will be futile. Customer engagement may include visiting your website, signing up for your newsletter, or visiting your physical store. Despite the variety of ways customers can engage with your business, most acquisition metrics are variations of the general formula below:

Acquisition = Engagement / Awareness

The Acquisition phase is perhaps the most well-understood phase of the entire model and there are plenty of pre-defined metrics available for this stage so, moving forward, I will not spend much time here*. To summarize, in the digital world acquisition is usually measured by click through rates from various advertising channels. However, other secondary metrics such as the change in traffic through a site from a specific channel, can also be used as a good proxy of acquisition.

In the offline world, even though there are no foolproof acquisition metrics, you can still measure acquisition through the Engagement/Awareness formula or simply use an engagement metric when awareness is hard to measure.

Activation

Activation describes the steps a business takes to encourage acquired customers to make their first purchase. Factors that determine the effectiveness of activation may include the efficacy of your website (measured by bounce rate), the attractiveness of your product (measured by customer surveys/interviews), and the customer’s experiences when trying out the free trial version of your software (measured by churn rate).

In general, the steps a business takes to activate a customer cohort may vary depending on the product/service offering of the business. For example, for e-commerce businesses important activation factors may include website landing page experiences, user behavior on site, and shopping cart abandonment rate.

Because activation metrics vary greatly by industry, the key to accurately measuring the effectiveness of your activation phase is to choose two or three key metrics that best describe the most important activation steps in your business. For example, a SaaS company might use its free trial signup rate, free trial churn rate, and free trial conversion rate.

Retention

Retention describes the process through which a business encourages past customers to continue making purchases now and into the future. This is perhaps the most important stage of a customer’s journey because for most companies it provides the largest source of revenue. According to research done by Adobe, 41% of total online revenue in the U.S. is from repeat customers despite the fact that this group only constitutes 8% of the total population. This information is also relevant when considering the single order view. Research by Bain & Co. has shown that in the apparel industry a customer’s 5th and 10th purchases are 40% and 80% larger than the customer’s first purchase. . Both of these statistics show that retaining repeat customers can provide an enormous amount of value to a business.

The above studies have already given us a hint that customer retention can come in two forms: buying the same product more frequently (purchase frequency) or buying more products in each purchase (average order value). Luckily, both metrics can be easily obtained from your e-commerce or POS systems, making it simple to keep track of and calculate which behavior your repeat customers are exhibiting.

In measuring retention, it is essential to capture both of these characteristics in order to fully maximize the value you obtain from your customers. Ideally, you want a customer to have both a high purchase frequency and a high average order value. If a customer has a high number for one of the values but not the other, it can be very valuable to initiate targeted marketing campaigns in order to raise the factor that the customer is lacking.

If both of your retention metrics are low, it might be a warning sign that the product or service you provide does not satisfy the needs of your customers or that you are not positioning yourself well in a fiercely competitive industry. In either case, this calls for a reexamination of the customer’s first purchase experience and perhaps your brand positioning relative to your competitors in order to increase retention metrics. The best method of reexamination may include customer interviews, customer surveys, and/or competitor research.

Referral

Now onto the most important but also the most commonly ignored step — Referral. The referral stage is so important that when I consulted for a weight loss company in China that spent millions of dollars on marketing annually, over 30% of their new customers were still coming from referrals.

I cannot emphasize enough how important the referral stage is for a business to produce organic growth in long-term revenue. Referrals not only provide the business with a healthy stream of customers at low to almost no cost, customers acquired through referrals also have a significantly higher chance of becoming repeat customers for your business. Furthermore, they, in turn, will refer even more customers. Most business owners know the importance of the referral stage, but the question is — what is the best way to measure it?

As of now, there is no method to measure customer referrals natively within your current IT system. However, referrals can be measured deliberately through customer surveys and/or the construction of referral programs.

The classic way of calculating a customer’s tendency to refer another customer to your business is called the Net Promoter Score. Even though this sounds complex, the Net Promoter Score is in fact fairly simple to calculate.

All you need to do is send out a survey to your current customers and ask them: “On a scale from 0–10, how likely are you to refer our product/services to a friend or colleague?” Customers are classified into different groups based on their answer:

  • Those who answered 0–6 are considered “unsatisfied customers”: unhappy customers who might damage your brand through negative comments.
  • Those who answered 7–8 are considered “indifferent customers”: customers who are satisfied with your product but will not spend any effort promoting to other users without strong strong incentives.
  • Those who answered 9–10 are considered “raving fans”: customers who love your product and will promote it organically.

The Net Promoter Score is calculated by subtracting the percentage of “raving fans” from the percentage of “unsatisfied customers” based on the survey respondents. It can range from -100% to 100%. A positive net promoter score means that customers are overall satisfied with your product and services and will refer it to other customers; a negative net promoter score means that your customer will not only not refer your product to other customers, they will have a negative effect on consumers that otherwise might have purchased your product.

The Net Promoter Score will give you a general idea of how satisfied your customers are with your product and how this affects their tendency to promote it. Using the survey responses, you can also strategically target different groups of customers to make the unsatisfied more satisfied, indifferent more active, and in order to keep raving fans raving..

However, while the Net Promoter Score can give you a general idea of how well your business is doing in terms of a customer’s referral tendencies, it does not offer a clear way of calculating the referral revenues of a specific customer cohort. For this, you need a referral program.

In fact, almost all major players in the consumer product world including Uber, HelloFresh, and Target, have some sort of referral program that both measures and facilitates continuing referrals between customers. Furthermore, direct selling companies such as Amway and Mary Kay Ash are designed around business models who rely heavily on referrals between customers.

Through referral programs these businesses can estimate how likely a customer is to refer others (the referral rate), and account for the revenue produced by those newly referred(average revenue per referer), thereby capturing the full value a referrer contributes to the company.

While referral programs can range from simple to complex, the principles remain the same. As long as the program 1) provides some incentive for customers to continually refer the product/service to their friends and 2) can offer the company a way of measuring how many people are referred by a single customer (average referrals per customer), it is a good referral program.

Even though referral programs can only capture the tip of the iceberg regarding this process, it can still be both profitable and valuable. According to a study published by the Harvard Business Review on German banks, customers referred to a bank are 18% more likely to stay with that banks and generate 16% more in profits compared with the average customer. Lastly, it’s worth noting that referral programs cost significantly less money than marketing efforts in the acquisition phase.

Revenue

Finally, let’s talk about revenue. In this model, revenue is not a process but rather a repository into which all pathways flow. If we were to picture all pathways in this model as rivers in the customer journey, revenue is the lake where they all eventually converge. There are three primary “pathways to revenue” that can help us calculate customer lifetime value quickly.

  • Acquisition -> Activation -> Revenue: this is the “first purchase” pathway, describing the customer’s journey to their first purchase with the business. This is usually the only pathway businesses consider when calculating marketing ROI. However, this pathway does not capture the lifetime value of a customer cohort.
  • Acquisition -> Activation -> Retention -> Revenue: this is the “recurring purchase” pathway, describing a customer’s recurring purchases with the business. For industries like e-commerce, a large portion of a customer’s revenue contribution is made through this pathway. Therefore, it is crucial to calculate the revenue value of this pathway to understand the full contribution of a customer cohort.
  • Acquisition -> Activation -> Retention -> Referral -> Activation -> Revenue: this is the “referral purchase” pathway. This pathway includes the revenue contributions described in the previous pathways as well as those made by the people who were referred to the company by the initial cohort during their relationship with your business. When comparing the two previous pathways this one is less obvious but can serve as an extremely powerful internal acquisition machine that can produce a healthy revenue stream for your business without any external marketing efforts.

The third part of this blog post is going to offer a concrete example of how to apply this framework to business cases while also describing some important guidelines to keep in mind when choosing metrics. Meanwhile, if you have any questions, please feel free to email bill@humanlytics.co or visit humanlytics.co. To view the full blog post, please visit this link.

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Bill Su
Analytics for Humans

CEO, Humanlytics. Bringing data analytics to everyone.