Footfall and In-Store Conversion Analysis

In-store conversion rate = (Number of transactions ÷ Number of visitors) × 100

If 200 people enter your store and 40 make a purchase, your conversion rate is 20%.

Conversion rate is one of the most important retail metrics because it separates the volume of opportunity (footfall) from your ability to convert it (staff performance, merchandising, product range, pricing). A busy day with low conversion is different from a quiet day with high conversion — and the solutions are completely different.

AskBiz can analyse conversion rates if you have footfall data. Sources:

People counters: door-mounted sensors (Axis, RetailNext, Dor.com, Counterpoint) that count entries and exits. Most modern systems offer API or CSV export.

Wi-Fi analytics: some POS systems and store Wi-Fi providers estimate footfall via device detection. Less accurate than door counters but often already installed.

Manual counting: for lower-budget operations, staff can count visitors manually using a clicker counter. Even rough data is better than none for trend analysis.

Upload to AskBiz: import footfall data as a CSV (date, store, visitor count) and AskBiz will automatically calculate conversion rate by overlaying your POS transaction data.

With footfall and transaction data combined, you can identify:

• Conversion rate by hour — are you converting better in the morning or afternoon?
• Conversion rate by day — is Friday busier but lower-conversion than Saturday?
• Conversion rate during promotions — do promotions bring footfall without proportionate conversion?
• Conversion rate by staff shift — high-performing staff often show in higher conversion during their shifts

Ask AskBiz: *'What is my in-store conversion rate by day of week over the last month?'* or *'Compare my conversion rate during the January sale vs the two weeks before.'*

If your conversion rate is below 20–25% (benchmark varies by retail category), common causes and solutions:

Pricing concerns: customers browsing but not buying may be comparing online prices on their phone. Consider a price-match policy or in-store-exclusive pricing.

Staff availability: if conversion correlates with staff-to-customer ratio, adding floor staff during peak hours pays back in conversion.

Merchandising: poor layout means customers can't find what they came for. A/B test product placement and measure conversion impact.

Stock availability: if popular items are frequently out of stock, footfall converts to disappointment rather than purchase. AskBiz tracks out-of-stock frequency — ask: *'Which products have the highest out-of-stock rate in-store?'*