Decoding Essential eCommerce Strategies: Segmentation vs Classification Uncovered

In an ideal world, everyone who wanted your products and services would easily find your website, add what they needed to their cart and check out right away. There’d be no omni-channel journeys, no competitor comparison and a very clear target customer who was always happy to engage with your brand.

Reality can feel like a dagger straight to the cart.

While some products will have a much broader appeal than others, it’s very unlikely that you’ll ever be able to sit back and wait for clients to come to you. Instead, you’ll need to identify precisely who is likely to want to buy from you and then devise a clear strategy to effectively target those consumers. You’ll need to do that in a way that feels personal to them and compels them to buy from your brand - ideally, on a regular basis.

That’s a pretty tall order for any one human being to meet. A real pain in the pixel, some might say.

Luckily, help is at hand in the form of AI, segmentation, and classification. Together, these technologies can help you to achieve marketing efficiency, nurture customer loyalty, and improve overall sales performance. Don’t believe us? Research suggests that AI can reduce customer acquisition costs by around 50%.

We’ll be covering everything you need to know about segmentation vs classification in ecommerce in this article:

• What is segmentation?
• What is classification?
• What is the strategic value of correctly implementing both?
•  Why do we choose to use classification?

What is segmentation?

Segmentation is the process of dividing a customer base into distinct groups based on similar characteristics, preferences, or behaviours. The goal is to identify meaningful subgroups within a larger customer population.

That could mean creating groups of customers based around age, gender or location, Or, by values and beliefs, by the type of device used or by purchase history and buyer habits. There’s lots of different options but they’re broadly split into four models. 

Don’t worry, no one is suggesting that you sit at your desk and manually create individual customer segments from scratch. With tens of thousands or even millions of customers to trawl through, that would be mission impossible. Instead, AI can be used to make informed decisions about what segments are needed, and who should be placed in each. The benefits of this include:

Increased personalisation

With your customers neatly segmented into manageable groups, you can deliver more precisely targeted experiences to them. That translates directly into cash in the bank, with research suggesting consumers spend an average of 36% more as a result of a personalised experience. What’s more, 56% of consumers say they will become repeat buyers after a personalised experience – that’s an increase of 7% in the last 12 months[1]. 

Enhanced customer experience

Segmenting customers can also enhance the overall shopping experience, which creates a positive brand impression and builds loyalty. Offering more relevant product recommendations, appropriate promotions, and a more tailored user experience, ultimately improves customer satisfaction levels.

Better product recommendations

Segmentation can be used to provide personalised product recommendations to customers based on their segment's preferences, purchase history, or browsing behaviour.

More successful pricing strategies

Segment-based pricing strategies can be implemented in the form of customised pricing or varying discounts and promotions across segments.

It’s clear that segmenting customers can be an effective tactic for any customer-centric marketing strategy. So, let’s dive into the classification portion of segmentation vs classification in eCommerce (*spoiler alert: classification can deliver even greater marketing efficiency).

What is classification?

Classification goes beyond sorting customers based on attributes they possess now. It looks towards the future. Think of it as your eCommerce crystal ball. 

So what is classification exactly? Simply put, classification is a special form of prediction. Here at QUIN, we use classification to predict what the future state of a customer may be. Will they churn or not churn? Will they complete their purchase or abandon their cart? 

More targeted marketing

Classification helps eCommerce businesses to devise and implement tailored, targeted marketing strategies which are aligned with the likely future actions of customers. 

Knowing ahead of time that there is a high probability that a customer will abandon their cart rather than completing the check out process means you can deploy tactics to reduce that risk. That could look like targeted codes or incentives - such as discount coupons or free shipping for example - to nurture that shopper through to the conversion stage.

What is the strategic value of correctly implementing both?

Implemented strategically, segmentation and classification can improve customer engagement levels, boost conversions, and grow sales.

Segmentation focuses on dividing customers into distinct groups based on specific attributes, pattern recognition, buying habits and previous behaviours. This means marketers can create more targeted campaigns and deliver more personalised eCommerce experiences.  

By accurately segmenting customers based on their preferences, behaviours, and characteristics, businesses can gain deeper insights into their target audience. This understanding allows them to tailor marketing messages, promotions, and product recommendations specifically to each segment's needs and preferences.

Classification removes uncertainty and guesswork. It allows you to understand how a customer may behave in the future, so you can develop targeted marketing strategies aligned with those expectations. 

By combining the power of segmentation and classification, businesses can gain a deeper understanding of their customers, optimise marketing efforts, enhance the user experience, and make data-driven decisions allowing for optimal business outcomes in the eCommerce sphere.

Why do we choose to use classification?

While segmentation is valuable for understanding and predicting customer behaviour and personalising marketing efforts, it involves dividing cases or data into different groups based on similarities. This is typically done by comparing new cases to past cases that have already been categorised - as long as these cases are similar enough.

However, if a new case is significantly different from the known cases, existing segments may need to be reevaluated, leading to the creation of new segments or updates to the existing ones. In large and constantly changing data environments, it's simply not practical to reexamine all past data for each variation.

Classification goes beyond the information we already know about a customer - such as their age, location or buying habits - and predicts what future interactions may look like. This is an invaluable tool which removes the guesswork associated with wondering what shoppers may do next. Invaluable for planning and strategy, classification outlines what lies ahead, so there are fewer surprises and fewer unsuccessful marketing deployments further down the line.

When it comes to segmentation vs classification in eCommerce, do you favour one concept over the other, or do you use both strategically to generate the best possible outcomes? Let us know in the comments.

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[1] Source: https://segment.com/pdfs/State-of-Personalization-Report-Twilio-Segment-2023.pdf