The practice of tracking consumer behavior through group types and characteristics over time is known as cohort analysis. These grouping characteristics can include categories such as the date of purchase of items as well as the duration spent on the mobile application. You may also create your categories based on the needs your business has identified from tracking your consumers’ behavior. Sounds interesting? You can also read more here about proper cohort analysis and retention on verfacto.com.
Cohort analysis is a severely underutilized tool in the e-commerce industry. It has a huge potential to generate great amounts of revenue for retailers and its implementation can be a game-changer for many. It also provides for a clearer distinction between growth and engagement, as different datasets can help brands better visualize the hard numbers their business has been generating.
Here are some of our top tips for utilizing cohort analysis to grow your business to greater heights and bring in extra revenue through increased sales.
1. Retention Curve
A retention curve is a tool that tracks how the rate of engaged customers over time. This allows your brand to better understand your churn rate as well as determine the best cases to maximize retention rates.
Furthermore, it allows businesses to have an accurate data-driven representation of the actual number of customers it has managed to engage over a specified period. Good businesses tend to have a visibly greater retention rate over a given period compared to bad businesses.
2. Optimizing Campaigns Based on Consumer Types
Cohort analysis further allows brands to determine how best they can tailor their sales and marketing campaigns toward the behavior types of their consumers. For instance, consumers who spend a long time on the mobile application may receive different ads and tiers of discounts compared to consumers who are simply casually browsing and don’t indicate an intention to make purchases.
Segmenting customers based on specified characteristics has the added advantage of allowing businesses to tailor ad content for each group of customers. Cohort analysis, therefore, allows brands to develop actionable insights into the behavior of their consumers and how they can improve on their existing campaigns to better serve their customers.
While your competitors might be struggling with determining how best to optimize content to customers who are regular versus customers who have just joined their platform. Utilizing cohort analysis greatly simplifies the process for your brand in answering these seemingly complex questions — all by having this data-driven problem-solving tool in your arsenal.
3. After-Sales Support
Online merchants may have a regular base of loyal customers who return frequently to make purchases. These customers would benefit from excellent after-sales service to address their needs and concerns regarding their purchases.Cohort analysis allows brands to identify these loyal customers and categorize them based on their level of loyalty. For instance, customers who return regularly may receive extra updates on upcoming sales as well as added loyalty or membership points which they can redeem for discounts on their purchases.
Without a stellar after-sales support service network, a brand may eventually lose its existing loyal customer base to its competitors.
4. Discount Analysis
Cohort analysis further allows brands to segment their customer population into different groups to determine how the presence of discounts (or lack thereof) has an impact on customer loyalty. Almost like a scientific experiment, businesses can use a test group and a control group to conduct their discount analysis tests. Businesses can also track how different discount rates have an impact on the number of customers who return, thereby allowing for optimization of discount rates offered to customers without negatively affecting revenue.
5. Welcome Treat
Something many companies do is offer a welcome discount sometimes called a “welcome treat”. These companies usually do this through pop-up ads on their mobile applications or websites, offering flash sales, limited-time coupons, and usually including the phrase “for new users”.
The trick here is that before continuing, users have to state relevant information about themselves like shopping style, body type, and budget. These pop-up discounts may also require the user to sign up for a mailing list before getting the coupon code.
Cohort analysis can then be utilized to group customers based on their indicated profiles. Cookies on the browser will also tell you, based on what they indicated, what they ended up purchasing, and marketing material can then be optimized based on this information.
6. Rationing Discounts
Giving away discounts blindly may negatively impact profit margins for online retailers and hurt their long-term operational prospects. Cohort analysis allows businesses to identify which customers do not have the potential to be loyal or return, and thus give discounts on an expiration basis.
The upside to this is that customers who are irregular might not even use those discounts, thus allowing businesses to better manage their profit margins while not shying away from giving regular discounts to customers who are returning and loyal.
7. Better Manage Customer Acquisition Cost
Customer acquisition costs continue to rise with time, as the eCommerce industry grows increasingly saturated and businesses have to compete for consumers’ attention. To combat this issue, cohort analysis allows businesses to better visualize their returns on their marketing investments (ROMI).
It would be counterproductive to make investments in ad campaigns that have a negative return on investment. As such, utilizing a ROMI metric allows businesses to make better projections on how effective a particular marketing campaign would be in attracting new customers as well as retaining existing ones.
8. Data Segmentation
Grouping customers based on similar characteristics offers a tremendous advantage to any eCommerce business looking to find a better way to optimize their content and campaigns based on what customers desire.
Aside from customer segmentation, businesses can also consider categorizing their data based on attributes such as marketing campaigns and their own product catalogs. This allows businesses to look at how each specific group of customers behave in relation to their products and content and thus allowing sales and marketing teams to optimize on-site engagement.
Conclusion
The world of online retails stands to greatly benefit from using cohort analysis to understand its consumers better and generate greater revenue. Comparing different datasets allows for a much faster decision-making process in a rapidly evolving eCommerce industry.
These tips highlight some of the ways businesses can incorporate cohort analysis into their decision-making and sales and marketing campaigns and the potential benefits to be reaped, thereby growing eCommerce brands to greater heights.
Taylor is a freelance SEO copywriter and blogger. His areas of expertise include technology, pop culture, and marketing.
