Store Manager's Job: Customer Management Part 4 - Data Utilization

Now, the final part of customer management is about data utilization.

I will talk about how to avoid 'analysis for the sake of analysis' and how to effectively use the results of your analysis.

<For new customers>

Within 30 days of their first purchase, send an email saying 'Thank you for visiting and purchasing,' provide information on repeating cosmetic purchases, send a 10% off coupon for their next visit, ask for feedback by saying 'Could you tell us what you liked or disliked?', or connect to the next proposal by asking 'How are you finding the product?' or 'A new product from the brand you purchased has been released.'

<For repeat customers>

To increase the repeat rate, encourage return visits by issuing membership cards, point cards, stamp cards, or discount vouchers for the next visit at an early stage, such as on their second visit.

In the case of cosmetics, estimate when they might be running out and send an approach email or send a video on how to use the product via LINE or other platforms.

When serving customers, use data to understand their preferences and past history. Saying things like 'Thank you as always,' 'You chose this color last time, so how about this one today?', 'This is very popular right now,' or 'A new shade of foundation that would go well with the lipstick you bought last time has been released; would you like to see it?' will make the customer feel happy that you remembered them.

<For premium customers>

To make them feel like a VIP and give them a sense of superiority, it is a good idea to hold VIP-only events, new product launch parties, or offer early access to new releases.

There is also a strategy to increase new customers by offering benefits for recommendations on social media or friend referrals.

It is also good to send birthday cards with coupons, or on anniversaries, offer a re-proposal along with a memory, such as 'Congratulations,' or 'You bought this at this time last year, so how about this one this year?'

<For dormant customers>

Sending a 'long time no see' email to check in with a 500 yen return-visit coupon, or asking those who have stopped coming why they stopped via a survey, is also useful.

<For product and service improvement>

Use the basket effect to increase products that are bought together, place impulse-buy items around the register, make best-selling products stand out more, organize items that aren't selling, offer premium products to high-spending customers, offer affordable products to low-spending customers, provide attentive service to high-LTV customers, and provide efficient service to low-LTV customers to respond to each accordingly.

Please see the previous article for LTV analysis.

<Based on predictions>

You can propose products they are likely to buy next, follow up in advance with customers who are about to stop visiting, put out featured products on days when they sell well and set other prices higher, or hold discount sales on days when sales are slow.

<Summary>

We will verify these results at a later date, confirm which ones were effective and which had a weak response, and then use that information to develop the next set of improvements.

The key is to think about "who" you are communicating with, "what" you are communicating, and "when" you are communicating it.

Rather than introducing expensive and complicated software, simply starting with easy steps will make a world of difference in the results.
It really is just a small thing.

Keeping data simple, making input easy, utilizing it in small ways, and ensuring it is implemented and continued is what is truly important.

Thank you for reading.
I would appreciate it if you could like or follow.
I look forward to your continued support.

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