Why is the Question “Why?” so Important? Especially in Retail
We all want to make the right decisions. But how do we find out which decisions are right in retail?
Some of us have been trying to “try and fail” since our childhood, while others have learned to observe our surroundings and learn from the more experienced ones. Today, we all make it a little easier, because, with digital technology, we can measure almost anything. And when we have data – we are able to decide. Is it right?
The most successful Retail networks are overly obsessed with different metrics. Let’s call the data they collect with operational data – O-Data. They are records of what happened, what was achieved (or not). We then divide these into different groups and evaluate whether we meet the specified KPI’s. In Retail, there are many, but some of the most important ones are the following:
- Conversion rate
- Yield per m2 (if you still have stone stores)
- Gross versus net margin
- What revenue do you have per employee, or product lines or products
- Average shopping cart
- How many products are in the average cart
- Online/offline sales ratio
- The year-on-year increase in sales
- Break-event point
- Customer retention
- Customer loyalty
- Customer satisfaction or Customer Experience
Consequently – every one of our decisions – whether a marketing campaign or promotion of a product should be based on this data. But is this the right way (of course, if this data is correct)? Yes and no.
And most companies do so. It is much better than making decisions based on assumptions, feelings, or how we slept. Some of the extraordinary people of us can do this – we call them the ones with the 6th sense – developed intuition. But do we all have it? I suppose not. And they are never 100% reliable either. An approaching divorce, a very stressful situation, and intuition suddenly hid somewhere.
But “having intuition” would be compared to buying a new tablet. As a buyer, you now have the ability to view and decide on dozens of reviews. Decide on the experience of other people. And decisions based on experience tend to be the right ones. Not based on one or two reviews, which may be a statistical error, but let’s say based on hundreds of reviews.
Now imagine that you would have such data not as an ordinary individual – buyer individual, but as a retailer – Retailer. What you care about is then much, a much wider scope. For example:
- Why did the buyer put this product in the basket?
- Why didn’t the customer buy anything?
- Why do two stores in the same town have so different sales? Is the staff responsible? Or a location?
- Why is one product selling great but another very similar and more profitable for you so poorly?
- Why is my brand so popular in the 30-45 age range?
- Why do two sellers in a single store have such different sales? Is it because of their knowledge, or their attitude, or the cleanliness of their teeth?
- Why did an excellent employee leave us, even if there was nothing to suggest so?
- Why are only older people reporting to our ads?
For simplicity, let’s name the answers to these questions X-Data (Experience Data).
If you had such data, would it make your decision-making easier? If you only use O-Data, you respond to situations. If you also have X-Data, you can predict situations.
Now imagine that there is a system that will not only help you collect this X-Data, but will also combine it with your O-Data. Not only a small sample, but it can “eat” a huge amount of this data. This is where the so-called magic begins, or the artificial intelligence with such a boom today. In this case, it will show you facts and links that you had no idea about.
All through easy-to-understand dashboards, conclusions, and recommendations.
What will be your task?
Just think carefully about which KPIs are most important to you in which area. Together we set up the system so that everything goes automatically. It will then show you how you are approaching KPIs and what to do.
For example, even the little things that the cleanliness of your retailers’ clothing has an x percent impact on the return of the entire store. Or how much money you need to invest in a particular training if you need to increase your agents’ NPS by 10%. Everything can be watched as it evolves over time, what are the trends and, say, how you are in comparison with your competition.
Are you interested? Do you still think it makes sense to make decisions in Retail based only on existing data? It will be my pleasure to show you the huge possibilities of making the right decisions if you start collecting Experience data as well. It is the Qualtrics system that is used by more than 11,000 customers worldwide (including Google, Amazon, or Microsoft, as well as many small and medium-sized companies). Not only for customers but also for employees. The average ROI is over 600%. Anodius is a certified local (SK, CZ, PL, HU) partner of the Qualtrics system.
Miroslav Procházka, CX solution manager