Are you customer engagement strategies bringing in the results you are expecting? If not, you are at the right place, because by the end of this article, you will have insights into improving customer engagement in e-commerce.
You can only improve customer engagement and loyalty if you understand customer behaviour in detail. But how can you achieve that?
Cohort analysis is an essential technique for e-commerce businesses to understand customer behaviour. It empowers businesses to identify trends in customer behaviour and collect actionable insights by grouping them based on shared characters.
Let us explore how cohort analysis is the key to understanding customer behaviour.
What is Cohort Analysis?
Cohort analysis is a market analysis in which customers are classified according to similar characteristics or events during a certain time. These groups, or cohorts, create the possibility to study certain segments of users and their behaviour within business over a given period of time.
For example, you could create a group of customers who, for the first time, made a purchase in January and then observe their subsequent purchases. The output of this analysis gives a better vision of each customer segment in terms of customer retention, engagement, and lifetime value.
What is Cohort Analysis in E-commerce?
Cohort analysis can be used by e-commerce brands to identify those customers who are the most likely to return, the promoting campaigns attracting the highest value customers, and the product categories that can generate the most repeat sales. Such granularity is incredibly useful when it comes to making business about the inventory and the money spent on personalised marketing and customer retention.
This analysis is particularly powerful in e-commerce as a whole. When comparing one group to another throughout the year, companies have insight into which efforts to maintain, change, or abandon in regards to customer relations.
TechMonk: The Best Cohort Analysis Tool For E-Commerce
Why is Cohort Analysis Important?
Cohort analysis offers multiple benefits for e-commerce businesses, including:
- 1. Accurate Customer Lifetime Value (CLV) Predictions: Cohort analysis allows for proper quantification of the CLV of the differentiated customer groups.Thus, brands know which cohorts are the most valuable over time and make exact sales predictions and shift their acquisition strategies to target high LTV customers.
- 2. Pinpointing Churn Reasons: Cohort analysis also enables e-commerce brands to determine when and why customers lose interest or stop buying. If these areas were resolved earlier, they would reduce churn rates, hence the term "churn points" or "churn factors."By evaluating these change points, it is possible to undo them using either product changes, customer care services, or reinvention campaigns.
- 3. Data-Driven Personalisation: Businesses can develop accurate marketing niche segmentation to market to individual customer cohorts.This could mean giving customers coupons, sending them specific emails, or simply recommending something to them, thus making customers feel wanted and more likely to buy again.
- 4. Enhanced Inventory and Supply Chain Management: Seasonality plays a critical role in consumers’ purchases, and it is essential to know which products or categories several cohorts prefer over others.As a result, businesses can tackle purchase frequency imbalances to prevent overstocking and stockout situations. This helps in ensuring that stock is available when needed most, and also helps in minimizing operating cost hence effectively satisfying the users.
- 5. Efficient Budget Allocation Across Channels: By knowing how well the various groups do in different acquisition approaches, the e-commerce brands can properly distribute budgets.For instance, one of the client groups may record good results from social media campaigns, another from email marketing, thus efficiency of the resources used can be adjusted for the best ROI.
- 6. Supporting Long-Term Strategic Planning: Even based on the results of a single year’s cohort analysis, there are elements that can be important for the preparation of long-term work.In other words, if a brand can monitor how the customer uses the brand, then they can guess how the demand will change, when to change the prices, how to plan for marketing their products and how to cultivate customer loyalty programs according to customer expectations.
Ways to Use Cohort Analysis to Grow an E-commerce Brand
1. Increase Customer Lifetime Value (CLV) and Revenue
Customer Cohorts demonstrates which groups consistently provide the most value in purchasing patterns. Knowing the factors that cause consumers to continue buying, e-commerce brands can design actions to improve CLV and make consumers’ growing contributions to the business.
2. Optimise Marketing Channels
Cohort analysis can also indicate the marketing channels that attract valuable customers. For example, if the campaign increases user engagement in the long term among some category of users, brands may spend more money in the same channel in future campaigns.
3. Identify Seasonal and Discount Buyers
E-commerce sales vary at some point in the season or during promotions. Cohort analysis is done according to the purchase time, and it helps brands understand some buyers who buy products at a particular time of the year or some buyers who look forward to discounts.
4. Find Out the Most Effective Discounts
While offers affect the sales in a big way, not all customers are moved by offers/sales. Through the cohort analysis of the buying behaviors, marketers can identify which groups are most sensitive to certain discount levels in an endeavor to optimize the conversion rates for the brands.
5. Discover Repeat Purchase Products
Cohort analysis identifies which of the products are frequent in the market. With such products identified, brands can focus more in their marketing, stocking as well as recommendations in a bid to ensure customers come through the door again.
6. Enhance Email Marketing
Cohort analysis can help e-commerce brands make particular changes to their email marketing. For instance, if a specific cohort of customers is receptive to calls for specific products, brands can copy similar campaigns for other similar customers and enhance engagement as well as sales.
TechMonk: The Best Cohort Analysis Tool For E-commerce
TechMonk is a cohort analysis tool offering e-commerce brands valuable insights into customer behaviours. TechMonk provides a clear vision of how various customers and segments behave with the company and its brand over time.
TechMonk lets e-commerce businesses create cohorts based on Events and Customers. Here are some of the events-based cohort analyses on TechMonk.
- • Order-based events: Order delete, checkout create, order update, order confirmed, order out for delivery, order RTO delivered, order RTO initiated, order paid, and order placed.
- • Tickets-based events: Ticket update.
- • Product-related events: Product delete, products update, products create, and collections create.
- • Review-related events: Review request, review submitted, review approved, and review rejected.
- • Customer-related events: Customer update, customer conversation, customer create, and customer delete.
- • Cart-related events: Cart delete and carts update.
TechMonk also offers merchants an advanced filter for creating cohorts. This lets businesses micro-segment customers by applying different filters for segments, making the cohorts more precise. With this level of precision, they can easily analyse customer trends and create targeted AI-powered campaigns.
TechMonk is not a solution only for customer segmentation. It is a single e-commerce solution that combines all the necessary tools. It takes away the need for e-commerce businesses to subscribe to different tools, which is costly and it creates data silos.
- • Customer data platform: TechMonk creates a single source of truth for all customer data, eliminating data and intelligence silos.
- • Customer journey orchestration: TechMonk helps you orchestrate the journey of e-commerce businesses through automated events triggered by specific customer actions.
- • AI customer service: Ensure your customers receive uninterrupted support through our Gen AI bot that answers queries and offers personalised recommendations.
Want to know how TechMonk can make things easy for your business? Get on a call with us now!
Boost The Effectiveness of Your Targeted Campaigns With A Tool That Micro-Segments Your Customer Cohorts
Takeaway
Cohort analysis is also quite helpful when it comes to e-commerce brands, judgments and customer retention and all other essential decisions associated with marketing. When clients are divided into significant segments, brands may notice patterns that would otherwise go unnoticed, giving them the modification they need to achieve a more effective experience with their audience.
Cohort analysis is less about amassing the numbers; it is about interpreting them. This analysis provides brands with a greater understanding of what specific marketing channels, promotions, or products make customers more loyal, and thus enable organisations to maximize their CLV and fine-tune the ways in which they grow for the long term.
As e-commerce companies strive to do more with their data than basic tracking, cohort analysis provides a powerful method of examining and leveraging deep customer behaviour patterns.
FAQs
What is the difference between cohort analysis and segmentation?
What is cohort analysis with example?
How can cohort analysis improve marketing efforts in e-commerce?
Can cohort analysis help with customer retention?
