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Personalised Marketing Using Machine Learning

OVERVIEW - FMCG, RETAIL, LIQUOR ExAMPLE

A personalised customer experience is an invaluable strategy to increase sales, improve customer experience, and boost loyalty. Enabling personalised marketing analytics allows data to empower your marketing executives, sales team, and retail specialists to get the most out of customer information. 

 

With seasonality impacting FMCG, retail, liquor stores and pubs, it’s critical to keep a solid core consumer base and take advantage of seasonal peak periods to encourage higher sales. Knowing and understanding the what, when, and why of each buyer persona can effectively improve revenue.

 

Using existing store data, retailers can utilise Machine Learning to create customer profile, data-driven customer personas to cluster customers and understand their purchasing behaviours. With an ML-based predictive model, we are able to understand the customer’s most likely next action. Coupled with personalised marketing analytics, effectively push multi-channel offers and communications where and when the customer is most active.

GOALS

 

Establish AI-based customer segments through buyer personas

 

Increase revenue through targeted upselling and suggested selling (ROI)

Improve marketing strategy by predicting the next best action

 

Discover new business opportunities based on consumer behaviors and seasonality trends

data CONSIDERATIONS

KEY TECHNOLOGIES AND PROCESSESS

Train Artificial Intelligence to segment customers based on persona and buyer behaviour.

 

Use Machine Learning and Predictive Analytics to identity which products, promotions, and strategy will resonate to each segment for use in upselling and suggestive selling.

 

Identify environmental variables such as trends, new products, and seasonality for marketing leverage.

SAMPLE PREDICTIVE MODEL 1 - RETAIL GOODS

Personalised Marketing Analytics based on Machine Learning Predictive Analytics

SAMPLE PREDICTIVE MODEL 2 - LIQUOR

Personalised Marketing Analytics based on Machine Learning Predictive Analytics

results

Data-driven marketing strategy to match product with applicable customer segment and persona.

Increased effectivity of marketing efforts through predictive analytics.

Higher sales generated through improved upselling revenue and higher capture ratio.

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