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Council Post: The Big Refresh: Insights-led Segmentation Is The Next Normal

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The Big Refresh: Insights-led Segmentation is the Next Normal

Illustration by The Big Refresh: Insights-led Segmentation is the Next Normal

Imagine this scenario- a well-packaged mobile application or web page with an attractive interface but no customer traction. Unfortunately, this is the reality for many consumer brands today.  Despite packaging their products and services in a ‘cool’ manner, very few customers spot or use those products. The reason is, for a long time,  organizations have taken a market-oriented approach with narrow techniques to understand the customer. 

However, the digital world we’re living in has disrupted more than the technology for communication. More and more consumers expect brands to understand their preferences to engage and purchase. 

Companies can act on these changing consumer expectations is by creating a customer-centric strategy that puts the consumer at the forefront and creates value through the company’s offerings. This involves understanding the customer, their needs and creating a meaningful experience for the consumer on their terms. 

Customer-centric

Customer centricity is essentially putting the customer first and creating value for the customer. This goes beyond just providing the cool product/service at the point of purchase or offering gifts or coupons on a purchase. Instead, it is about an approach that looks at the total customer lifetime value and focuses on consumer retention. 

Brands need to collaborate behavioural science with insights-led segmentation to understand the customer well enough. They should be able to anticipate the consumer’s desires and create meaningful experiences.

More and more organizations understand the need to shift focus from mere campaigns and begin thinking about the customer. The challenge is to turn this blueprint into reality. Consumer brands might have the data, the technology stack, and the business processes in place. However, they cannot ensure that all of these work as a single unit. This is much easier said than done – such an insights-led approach can be cumbersome or nearly impossible without the right technology partner.   

So, what does it take to build a customer-centric engagement strategy and execute it at scale? The answer is an insights-led approach that begins with a deeper analysis of customer insights that help brands go beyond the broad norms of segmentation is essential.  

Insights-led Segmentation

The traditional segmentation models group customers based on their geographic, demographic, or behavioural traits. While these are great starting points to understand your customers, companies need to delve deeper into the customer’s context and analyze the overall interests, preferences, affinities, and lifestyle to understand the consumer’s overall identity.  

 Forward-looking brands lean towards an insights-led strategy to segmentation which involves a business framework with data at the foundational base upon which customer engagement decisions are made. 

The insights-led strategy involves analyzing and predicting customer behavior by leveraging analytics. Based on these insights, organizations can delve deeper and organize customers into homogeneous groups based on their personalities, lifestyle, beliefs, and choices – as displayed across the channels, and so on. Brands can also leverage an insights-led strategy to forecast a customer’s future needs and personalize their offerings towards fulfilling those needs. 

Such an approach minimizes errors and yields better ROI. Above all, brands can delight customers with relevant, in-the-moment messages every single time.

The Essential Steps To Implementing the Insights-led Segmentation

To execute a strategy based on insights, one of the most important steps is for brands to tap into the existing data. This involves gathering and analyzing data at scale and in real-time. This data can be leveraged for reactive insights and predictive capabilities to support marketers forecasting their customer preferences and being ready to engage at the right time. Secondly, it is essential to invest in the right technology to make the most available data. Invest in a comprehensive engagement stack that helps marketers build deeper analytics for quick segmentation without the need to code or rely on other teams. 

It is essential to consider that both the consumers and the technology for consumer engagement are evolving. Marketers need to stay on top of the trends and quickly shift to newer channels and touchpoints as their customers do. It is also essential to remain agile by analyzing customer behaviour across channels. Identifying consumers’ micro-moments across different channels can throw light on their wants and needs, and the organization can predict and work upon those. 

Once brands have their work set out for them, they should harness the power of personalization. This includes personalizing emails, promotional materials, targeted ads, or recommendations. This helps set brands apart from their competitors and become more customer-centric. 

Finally, having an omnichannel approach while reaching out to customers across the various channels they may move to and generate maximum engagement. Along with this, loyalty programs should also be channel agnostic to retain most customers. 

We have just touched the tip of the iceberg of what insights-led segmentation has to offer. Brands that have implemented this approach have witnessed faster growth in their customer engagement. The buyer behaviour is constantly evolving, making it integral for brands to innovate faster and keep up with the trends to stay in step with their customers and become the brand they can relate to.

This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill the form here.

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Nalin Goel

Nalin Goel is the Senior Vice President, Product at MoEngage Inc. Nalin established the vision for Machine Intelligence at MoEngage and has been instrumental in setting up the Customer Insights and Data Sciences team. He led the launch of MoEngage's Analytics Suite.
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