Geo-spatial analytics

Precisely map customer value in your target markets

Target growth potential with Area Prioritisation Engine

Empower your business with pin-point customer targeting

An Area Prioritisation Engine is a self-serve analysis tool – enabling your sales and marketing teams to target specific neighbourhoods, based precisely on the potential value by customer available in each area.

They’ll see demographic segments with profiles that support marketing messages, including product preferences and attitudes to pricing.

You can even see exactly where competitors outpace you, and target those customer bases with highest value potential.

Self-service analytics tool

Target by neighbourhood

Target profiles and preferences

Erode competitor value over time

Self-service analytics tool

Target by neighbourhood

Target profiles and preferences

Erode competitor value over time

Enable sales and marketing teams to target customers by potential value

How Area Prioritisation Engine works

Book a free demo and chat

If you’d like to see for yourself how Area Prioritisation Engine could work for your business, you can book a 30 minute call and see a live demo:

  • Optimised data – combines first party (owned by you) data, with third-party geo-demographic data and consumer mobility data, to identify customers with highest purchase value potential to your business.
  • Highest potential areas – maps customers and value on to your chosen market geography (country, state, town, postcode) creating a targeted customer acquisition plan.
  • Targeted marketing – adds channel preference data, and product preferences, to enable the right messages to the most valuable customers, in the right places.
  • Self serve reporting tool – a user friendly interface that provides your teams with ongoing update and analysis of their target markets, as they take actions and measure the outcomes.

We’ll show you how this tool has worked for a global retailer, and answer all of your questions to be sure that it can work for you too.

Area Prioritisation Engine in action

Frequently asked questions

Why is area prioritisation useful?

Analytics engines such as Area Prioritisation work by analysing customer data such as browsing history, past purchases, etc along with supplemented third party demographic information, to predict what products a user might be interested in, what channels they prefer to use, and how much money and how often they are inclined to make such purchases.

In this way, a business can identify who their most valuable customer opportunities are, and how much value they represent.

What role does consumer mobility data play?

Consumer mobility data uses permission based location data available from mobile devices, to analyse where customers shop, how often, for how long, and most importantly at which specific stores or brands.

This enables a business to create direct comparison analyses between themselves and all their competitors.

This mobility data plays a huge role in predicting channel, location and brand preferences, along with broader product preferences.

How do area prioritisation engines handle privacy & data security concerns?

Recommendation engines should implement data anonymisation techniques, encryption, and access controls to protect user data and address privacy concerns.

Beyond your own first party data, all supplemented third party data must be permission based and compliant with relevant local privacy legislations.

How can businesses measure the success of their area prioritisation engine?

Businesses should ensure that all targeted marketing campaigns implemented as a consequence of area prioritisation insights are tracked and measured, ideally using control groups, to identify subsequent response in consumer behaviours.

Examples of success metrics to track include email or social click-through rates, conversion rates in terms of response, visitation and sales, customer satisfaction and overall revenue, or even reductions in basket abandonment.

Useful resources to grow your customer value

Case study: Frosts Garden Centres – retail location analytics to beat the competition

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Location analytics in retail

What is location analytics?How can location analytics help my business?How does location analytics…
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Case study: IKEA Thailand – customer engagement & modelling

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Do you need to win new customer more efficiently?

Improving your sales and marketing with highly targeted, relevant communications will drive reduction in cost per acquisition, and increase in order values and customer loyalty.

If you’d like to discuss your specific requirements, just get in touch here:

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