Personalised Marketing Using Machine Learning

A personalized customer experience, driven by machine learning and predictive analytics, enhances sales, loyalty, and marketing effectiveness in FMCG, retail, and liquor sectors.

Request Consultant

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

MACHINE LEARNING DATA CONSIDERATIONS

Point of Sales
Consumer Database
Inventory and Product Mix
Frequency of Visit
Membership or Loyalty Program Database
Industry trend and seasonality

KEY MACHINE LEARNING 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 2 – LIQUOR

SAMPLE PREDICTIVE MODEL 1 – RETAIL GOODS

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.