People & place analytics

Find your next best customers with Area Prioritisation

Pinpoint where to invest your efforts to maximise revenue growth and marketing ROI

Finding your next best customers

Ikano Insight’s Area Prioritisation Engine tells your business exactly where to invest sales and marketing effort to maximise growth, revenue and ROI.

YOUR QUESTIONS:

  • Where are the most valuable customers who don’t buy from you today?
  • How much potential value are they to your business?
  • Where should you begin – focusing and prioritising your efforts?

Area Prioritisation answers those questions and more!

Find you next best customers with Area Prioritisation Engine

How it works

We use a small amount of your aggregated, anonymised data – like your deliveries by postcode, or how many of your members live in a given district – and our proprietary algorithm provides you with a ranked list of neighbourhoods which hold the most potential for you, alongside exactly how much value you can expect to unlock.

You provide one year’s worth of data for your chosen KPI(s), grouped by postcode to which they are attributed, for example sales for deliveries to a given postcode.

We respond with either:

  • A recommendation report, specifying which areas hold exactly how much potential value for your business, and detailing the characteristics of neighbourhood profiles to support your targeted marketing.
  • An interactive dashboard, allowing you to analyse the characteristics of each area and to explore your results in more detail to maximise their impact.
Find you next best customers with Area Prioritisation Engine

Want to know more?

Book a 30 minute demo call to see first-hand how Area Prioritisation worked for a global retail brand, and chat to us about how it can make the most impact for you – or scroll down to review our pricing and FAQs

Area Prioritisation Engine in action

How it’s priced

 

It’s very simple. You tell us 4 things:

  1. Specify your chosen KPI measurement(s). (Eg. online purchases sales value, or growth in loyalty members.)
  2. Choose how far into the future you’d like to predict potential (priced per 6 month periods).
  3. Decide how often would you like to refresh your report (to update output following your market efforts).
  4. And finally, whether you would like a single report output, or access to a self-serve, interactive dashboard

The table below outlines costs based upon the above.

Area Prioritisation Single KPI measurement
(Eg. online sales)
Per additional KPI measurement
(Eg. in-store loyalty scheme member sales)
Set-up
Modelling & analysis
(6 month forecasting period)
£3,825 £985
Data refresh
Optional data refresh to reset versus targets £2,950 £565
Output
Recommendation report
single output and on each refresh
£2,750 £388
Interactive dashboard
annual cost per KPI measured
£5,950 £955

Area Prioritisation: Set-up

Single KPI measurement
(Eg. online sales)
:

Per additional KPI measurement
(Eg. in-store loyalty scheme member sales)
:

Area Prioritisation: Modelling & analysis
(6 month forecasting period)

Single KPI measurement
(Eg. online sales)
: £3,825

Per additional KPI measurement
(Eg. in-store loyalty scheme member sales)
: £985

Area Prioritisation: Data refresh

Single KPI measurement
(Eg. online sales)
:

Per additional KPI measurement
(Eg. in-store loyalty scheme member sales)
:

Area Prioritisation: Optional data refresh to reset versus targets

Single KPI measurement
(Eg. online sales)
: £2,950

Per additional KPI measurement
(Eg. in-store loyalty scheme member sales)
: £565

Area Prioritisation: Output

Single KPI measurement
(Eg. online sales)
:

Per additional KPI measurement
(Eg. in-store loyalty scheme member sales)
:

Area Prioritisation: Recommendation report
single output and on each refresh

Single KPI measurement
(Eg. online sales)
: £2,750

Per additional KPI measurement
(Eg. in-store loyalty scheme member sales)
: £388

Area Prioritisation: Interactive dashboard
annual cost per KPI measured

Single KPI measurement
(Eg. online sales)
: £5,950

Per additional KPI measurement
(Eg. in-store loyalty scheme member sales)
: £955

Additional options

  • Strategic recommendations and results presentations can also be provided, priced on application – or with a set price if regularly scheduled – according to the number of data points and locations assessed.
  • KPIs split into categories – for instance sales by product range – can be priced separately, as it’s likely to work out cheaper than pricing each KPI individually. You’ll also have more utility within the tool.
  • Discounted subscription commitments are available based on a percentage of agreed price.
  • Additional demographic data can be integrated on request, and priced separately.
  • If you’re not confident in the quality of your address data, our standard one-off cost is £975 for QA and aggregation.
  • If custom ETLs need to be developed in order to aggregate a complex transactional or membership database, or to automate data flows for benchmarking purposes, we can price this following a short assessment.
Area Prioritisation Engine pricing bundle examples

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

Read more

Location analytics in retail

What is location analytics?How can location analytics help my business?How does location analytics…
Read more

Case study: IKEA Thailand – customer engagement & modelling

Read more

Do you need to win new customers 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:

This field is hidden when viewing the form

Section Break

This field is for validation purposes and should be left unchanged.

© 2025 Ikano Insight. All rights reserved