Discount will be available on selected products
0$0.00

No products in the cart.

helping grocery retailers to identify their conversion funnel


Introduction

When it comes to getting a promotional campaign right, nothing is more important than having the right information. This is where in-store analytics come into play. We talked about this in our previous post. Now we are going to take this a step further and analyze the conversion funnel of some of the products shown in the promotional flyer we analyzed in our previous article and their effectiveness within the promotion.

An example of a supermarket’s flyer local campaign in the U.S.

One of the great advantages of our metrics is that they allow us to see the performance of the various products, as well as identify those that are not receiving the attention we expected. Thus, we will review as well some actions marketing managers can implement in each step of the conversion funnel in order to improve the numbers.

It should be noted that when it comes to e-commerce platforms, it is much simpler to analyze the information of incoming customers as there is a higher number of metrics to use. However, with these analytics, we can apply different metrics within physical stores to gain the desired results.

Analysis of promos

Let’s start by taking a closer look at the data gathered from the promotion. It should be noted here that for marketing managers, the conversion funnel is another interesting analysis to take into account in order to see the effectiveness of in-store promotions. 

 

Penetration

Bounce

Browsers

Engaged

Conversion rate

CSDs

19.9%

46.9%

53.1%

15.4%

12.1%

Avocados

11%

29.2%

70.8%

7.2%

2.4%

Milk

30.2%

55.2%

44.8%

22.7%

13.8%

Eggs

41.3%

65.2%

34.8%

20.8%

14.4%

Pillsbury gough

8.2%

46.8%

53.2%

2.6%

1.2%

Salmon

14.1%

16.2%

83.8%

6.9%

2.2%

Beer

20.4%

63.7%

36.3%

17.6%

14.1%

Post cereal

28.1%

29.5%

70.5%

10.4%

3.7%

Halo Top Ice Cream

10.6%

22.3%

77.7%

7.3%

1.1%

Smithfield bacon

8.2%

51.2%

48.8%

5.7%

1.8%

Meat

28.7%

20.4%

79.6%

21.3%

18.7%

To get a full view of what each section represents we are going to break down each of the metrics:

  • Penetration.- It refers to the traffic each section has received. This means that if we had 50,000 customers during the promotion, 9,950 have visited the CSDs section. This data is gathered with our in-store technology.
  • Bounce.- It shows the percentage of people who have spent less than 10s in a category.
  • Browsers.- It shows the percentage of people who have spent between 10 and 15s in a section.
  • Engaged.- It shows the percentage of people who have spent more than 15s in a section.
  • Conversion rate.- It shows the percentage of visitors to the grocery store who have purchased a specific product. For example, the 3.7% conversion rate for cereals means that from the total visitors we had during the promotion, 1,850 have bought this product.
Example of a supermarket’s layout with the penetration rates for each product

When taken as a whole, this information shows the process by which visitors to the grocery store end up being buyers of a specific product during their journey.

Next, let’s take a look at the data of the eggs and the salmon in order to analyze the funnel:

Eggs.- As we can see, this is a product with a high penetration rate. This indicates that most people visit this section during their journey to the supermarket. In the case of the conversion rate, it is high as well, which shows that most of the people have bought eggs since it is a basic product. If we look at the funnel, we come to the conclusion that from the 50,000 visitors during the promotion, 7,200 of them have ended up buying eggs.

Eggs’ conversion funnel

We gain some valuable information from both the bounce and browsers columns. The bounce column shows a high percentage, which means that most people spend less than 10s in the eggs section. This is not a bad indicator, since it means that people already know the brand they like and simply grab the eggs when coming to this section. On the contrary, the browsers column shows that not many people spend between 10 and 15s deciding what eggs to buy.

Salmon.- At first glance, we can see that the penetration percentage is quite low in comparison with that of the eggs. Thanks to this information we can assume that people do not buy salmon on a regular basis. Plus, the conversion rate shows that the percentage of people who finally bought the salmon is quite low – once again an indicator that shows it is not a product people tend to buy. From our total visitors, only 1,100 have bought salmon during the promotion, a figure significantly lower in comparison with the eggs.

Salmon’s conversion funnel

A closer look at the browsers column reveals that there is a high percentage of people who spend between 10 and 15s deciding whether to buy it or not. This usually happens with fresh products, since people tend to base their decisions on different aspects such as expiration date or appearance.

Depending on the product the percentages will vary. This is to be expected as basic products usually have high penetration rates, whilst fresh products or other products more “special” (i.e. ice cream) will have low penetration rates. In both cases, the conversion rate will modify accordingly.

Actions to implement

Broadly speaking, the conversion funnel shows the process of total visitors becoming buyers. Therefore, we will now analyse different actions we can implement in each step of the funnel in order to improve the numbers.

TRAFFIC

  • When we experience a decrease in our number of visitors, it could mean different things. We should take into account if the decrease coincides with holidays, which explains an occasional impact. Maybe a grocery store has recently opened in the vicinity, so people are comparing different alternatives and, thus, we are losing our target audience.

    If we notice a prolonged decrease, it could mean that people are resorting to delivery companies or online shopping instead of physically going to the supermarket. Whatever the reason, we should try to attract people’s attention once again, so we could try to increase our promotions and advertisements.

PASSERS-BY

  • Since this is the traffic received within a specific section, we should look for the main cause of a decrease in the visits. If we have a low penetration rate, this could mean that our section is being unnoticed by customers. Maybe it is because the posters that differentiate the aisles are not visible enough and people do not pay attention when passing-by.

    Another explanation could be that the section is too small and customers do not usually find what they are looking for. Hence, we should pay attention to these indicators and decide if we should broaden the section and the products available or redesign the posters in order to improve its visibility.

ENGAGED

  • At this point, neither a low rate nor a high one are good signs. A low rate shows lack of interest since people do not pay attention to our section. On the contrary, a high rate could mean that customers do not understand our product. Thus, if we notice that this happens, we could increase the number of shop assistants in this section so they can help customers with their hesitations and decisions.

    In any case, keep in mind that fresh products usually have higher rates because customers look carefully at these products as we have seen with the example of salmon.

CONVERTED

  • At the end of the funnel it is essential to look at the conversion rate. Usually, the price is the main aspect that prevents customers from buying. Therefore, if we have a low conversion rate we should carefully analyze if prices tend to be higher than normal.

    On the other hand, maybe customers do not end up buying our product because they do not like the format or because they do not understand it. A solution could be to launch food tastings or show cookings in order to bring clients closer to the products.

Once each step has been analyzed, it is important to identify at what stage people are losing interest in our product. It is always advisable to do benchmarking with similar stores in order to see if our funnel and rates coincide for the different categories. If we notice that our numbers are far from the average, we should implement the corresponding actions according to what has been previously explained.

Conclusions

Data is only as important as how it is used and interpreted. But the first step is to actually have the right data in the first place. This is where analytical tools show their worth. Not only do you get data on how each promotion is faring but you gain insight into why each performs the way it does.

This is critical for marketing managers to have in order to make informed decisions. Because they can easily identify which products are performing well and which ones do not meet their expectations. For the latter, there are actions they can implement in order to improve the results. For example, if they feel that customers do not understand a specific product, a solution could be to launch to showcase the various cooking methods. With this, marketing managers will bring clients closer to the product and it could turn into an increase in sales.

If you would like to take control of your in-store analytics and start making smart decisions on product promotions and general store management, it might be a good idea to get in touch and let us show you what our solutions can do for you.



Source link