Accurat’s Actionability Matrix helps retailers understand where they are gaining or losing market position, whether the change is driven by visitor reach or visit frequency, and which action to prioritise.

The matrix combines three metrics:

  • Fraction of Visitors: the share of market shoppers who visit your stores;
  • Average Frequency: how often those shoppers visit;
  • Share of Visits: your share of all visits in the market.

Together, these metrics show whether a retailer should focus on acquisition, repeat visits, loyalty, competitor response or expansion.

What is the Actionability Matrix?

The Actionability Matrix is a four-quadrant retail performance framework that combines changes in visitor reach and visit frequency with Share of Visits.

It answers three questions:

  1. Are you reaching more or fewer shoppers?
  2. Are those shoppers visiting more or less often?
  3. Is this strengthening or weakening your market position?

The three metrics are directly linked:

Share of Visits = Fraction of Visitors × Average Frequency

This means retailers can improve their market position by reaching more shoppers, increasing visit frequency or doing both.

What do the four quadrants mean, and which actions should retailers take?

Strong performance: reach and frequency are growing

In this quadrant, retailers attract a larger share of shoppers and encourage them to visit more often.

When Share of Visits also increases, the retailer is outperforming the market.

Recommended actions:

  • identify the regions, segments or store groups driving growth;
  • understand which campaigns, formats or propositions are working;
  • protect successful initiatives;
  • scale the strongest growth drivers;
  • monitor competitors to ensure the lead is sustainable.

When reach and frequency grow but Share of Visits remains flat or declines, competitors may be growing just as quickly or faster. The next step is to identify where they hold an advantage.

Frequency decline: reach grows, but shoppers visit less often

In this quadrant, the retailer attracts more shoppers, but those shoppers return less frequently.

Acquisition is working, while retention is weakening.

Recommended actions:

  • compare the behaviour of new and existing shoppers;
  • identify when and where repeat visits start to decline;
  • review pricing, promotions and assortment;
  • investigate changes in convenience or accessibility;
  • strengthen loyalty and reactivation programmes;
  • analyse which competitors are capturing the missing visits.

When Share of Visits is still increasing, stronger reach is temporarily compensating for lower frequency. This may be positive in the short term, but it can become a structural retention risk.

Fraction decline: shoppers are loyal, but reach is shrinking

In this quadrant, existing shoppers visit more often, but the retailer reaches a smaller share of the market.

The main challenge is acquisition rather than loyalty.

Recommended actions:

  • identify which audiences are no longer choosing the brand;
  • analyse regional or local gaps in reach;
  • improve brand awareness or price perception;
  • assess whether the store format and assortment still fit the target audience;
  • identify competitors gaining reach among the lost shoppers;
  • target acquisition and reactivation campaigns at underrepresented groups.

Strong visit frequency is valuable, but it cannot compensate indefinitely for declining reach.

At risk: reach and frequency are both declining

In this quadrant, the retailer reaches fewer shoppers and those shoppers also visit less often.

This is usually the most urgent position, especially when Share of Visits is also falling.

Recommended actions:

  • determine whether reach or frequency is declining fastest;
  • prioritise acquisition when fewer shoppers are entering the customer base;
  • prioritise loyalty and relevance when existing shoppers visit less often;
  • analyse performance by audience, region and store group;
  • compare the decline with wider market and competitor movements;
  • address the largest and most commercially important segments first.

A stable Share of Visits in this quadrant can mean that the entire market is contracting. This may protect the retailer’s relative position, but it does not remove the need to address the underlying decline.

How can retailers use the Actionability Matrix?

The Actionability Matrix can compare:

  • customer segments;
  • regions;
  • store groups;
  • store formats;
  • trading days;
  • competitors.

This helps retailers identify where growth is strongest, where acquisition is weakening and where repeat visits are under pressure.

For example, a large segment with strong frequency but declining reach represents an acquisition opportunity. A store group with growing reach but declining frequency may need stronger retention activity.

The matrix can also reveal competitor vulnerabilities. A competitor with declining frequency may be attracting shoppers without retaining their visits, while a competitor declining on both dimensions may create an opportunity to win over its customers.

Why should Share of Visits always be included?

Fraction of Visitors and Average Frequency explain what is driving performance. Share of Visits shows whether that performance is strong enough relative to the market.

A retailer can grow in both reach and frequency and still lose Share of Visits when competitors grow faster.

A retailer can also decline in both metrics while maintaining Share of Visits if the wider market contracts more quickly.

For this reason, retailers should always interpret:

  • the quadrant;
  • the direction of Share of Visits;
  • the commercial importance of the segment or retailer;
  • the wider market context.

From retail data to the right commercial action

The Actionability Matrix turns retail performance data into a clear commercial diagnosis.

By combining Fraction of Visitors, Average Frequency and Share of Visits, it helps retailers determine:

Where is the opportunity or risk?
What is causing it?
Which action should we prioritise?

This makes it easier to translate location data into focused acquisition, loyalty, competitor and expansion decisions.

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