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Case study

AI-led consumer segmentation in Saudi Arabia.

How Sila creates consumer clusters that share similar characteristics to employ strategies to engage.

The target audience of a food staple brand spans across all mothers in the region, but are all mothers the same? Obviously not.

How does a leading brand of a commoditised category build relevance by effectively reaching out to such a mass audience?

A leading food staple organisation with multiple brands of commoditised categories (packaged rice and cooking ingredients) was moving away from a blanket marketing strategy to a targeted approach.

Our approach focuses on understanding the different consumer segments. In this case, the different types of mothers responsible for cooking in Saudi.

Mayar foods (part of AlMuhadib) approached D/A and its Sila tool for this strategic need to identify and understand each segment and create a roadmap of the most effective strategies to engage with them.

The consumer segmentation in Saudi Arabia exercise.

With an audience-first approach, we understood the overall consumer picture. Around that audience, we build a machine learning model that divides the consumers into discrete groups with similar characteristics, such as personality traits, needs, values, and consumption preferences. We train the model with thousands of users and then use several algorithms (k-means, hierarchical and classification trees) to identify the optimal number of clusters. Historical posts are from each unique user; typically, the last 2000 posts get processed to arrive at the personality insights and the groups of people/segments that share similar characteristics.

D/A’s philosophy of consumer segmentation.

We believe in keeping it simple yet actionable. Our approach allows the segments we arrive at to be: 

  • Measurable: clear and tangible attributes and identifiers.
  • Sizeable: large enough to target, invest and benefit the brand.
  • Accessible: can be actioned and approachable via communication.
  • Sustainable: is not temporary; one that will be around.
  • Predictive: with access to historical data, an understanding of how segment sizes and priorities are evolving.

The output and roadmap.

5 unique consumer segments were identified, each of different size and potential that enabled the stakeholders to be more effective with spending towards the initiatives planned for each segment. For each of the segments, the team of researchers created a roadmap that included: 

  • WHO do you target → your audience segments, their significance and potential.
  • HOW do you target → the content and effective messaging.
  • WHERE do you target → the platforms and other touchpoints.
  • WHEN do you target → the timing, the duration.
  • WHAT do you target with → brand and SKU portfolio. 
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