How to Analyse Planograms & Measure KPIs for Visual Merchandising

Okay. Yeah, I see there is like a bunch of people already jumped in. So, uh we can begin. And thank you for joining, guys. And let me start with just the topic of this webinar. The topic of this webinar today is like in-depth analytics for planogram management. And first of all, uh let me introduce myself. Uh my name is Mark. I'm responsible for the business development uh at Leafio. And also one of the co-host of this webinar is Anna. Anna is the head of business development responsible for UK and EMEA. And Anna is a supply chain automation like solution expert. Hey, Anna. Hi. Hi, Mark. Hi, everyone. Yes, so uh Thank you for joining us. Thank you, guys. Yes. And first of all, uh let me just give you a few words about Leafio. And we have been working like with different retailers for more than already like than 15 years. And

currently like we have projects in 20 countries. We implemented more than 200 different projects. And at the moment we have around like 120 employees working in our team. And before we jump to the analytical block and show you like uh how we can analyze and what kind of the analysis do we have in our like solution, let me just provide you with a brief overview and tell you a little bit more about the platform. And Leafio is a platform like that automates the different area of supply chain with the help of AI and machine learning. And our platform currently like consists five different modules. And the first module that you are able to see in here, this is like our inventory optimization. And this module helps us to automate the replenishment processes like both at the level of stores and your central warehouses. And this module consists like powerful BI block in order to help your demand planners to identify the bottlenecks in

your inventory processes. Another block that you are able to see in here is our promotion intelligence tools. The promotion intelligence tools is like the solution that intended to manage all of your promotion activities and forecast all the sales for your promotion period. Uh another block in here that will be like the main topic of our discussion today is our shelf efficiency part. And this solution helps us like to cover end-to-end merchandising processes like starting with the planogram creation to this to the execution and analysis of your planogram. And this block and this module and solution like will help us to create the floor plan, put the equipment on the floor plan, and create the detailed planogram. And control and execute with the with the processes like with the help of our mobile application. And this module have a deep and powerful analytical block that we will show you a little bit later. And you will be able to see like what our solution has like as a different reporting parts.

So uh there is also assortment performance solution. That solution allows you to manage all of the assortments like create the assortment matrices, introduce and display new products to your assortments, aggregate your store by formats like as well track analytics and run some automatic like assortment approach. And the last but not least like our customer loyalty. This solution is fostered through different strategy aiming to attract new clients for you, new customers, and increasing the frequency of visit to your businesses, encouraging repeating purchases, and building the brand strength with the help of our like loyalty customer loyalty system. Okay, another thing that I want to cover for you guys. Like what are the benefits of using our platform? So, first of all, I want to mention that all of our solution like contains a powerful analytics with a large with a large number of different reports.

Also, uh all of our solution included like real-time decision-making data. And it's like mostly like driving the decision to with the help of AI and with the help of like some of the human interaction to make a good good and right decision-making process. And we are also like providing you not only like as a vendor, we are providing you with our like unified platform where you can like align of your assortment planning, like purchasing, and merchandising as well like merchandising processes in one place. So, our solution can be implemented like one by one or they can be combined between each other. So, that's why we're providing you like with unified platform and you can benefit like from all the modules that we have. As well, uh our solutions are customizable and you can tailor the platform to fit your unique like business requirements without any efforts involved. And our implementation team will make sure that

you will get like the seamless integration process and as well that well you will do like one time integration and you will be able to connect the other modules easily step-by-step at your own pace. So, if you if you can start like with shelf efficiency, later on you can add up the inventory optimization, then you will go with assortment performance and you you can add up and then build build yourself a personal like platform. And as well, like our solutions are designed for users and for all of the levels of users, like to enhance that usability for in enterprise, like wide benefits. And it's super intuitive tools, and you'll be able to easily use our solutions. And the next slide that I want to show you is like our shelf efficiency platform. There is just a few screenshots for you, and like our solution is like the planogram optimization solution that helps you to build the and manage end-to-end

merchandising processes. As I already said, like you can create the planogram, you can communicate it to the stores, and then you can end it with the execution and control of of your layout. And regarding the like what is our ideal approach and how the solution is supposed to work. So, we need to create the planogram, first of all. After that, we need to send your planograms to different locations, to store, to the businesses that you have, and then it needed to be executed at the location with the help of people that are responsible, with the managers' help, with the planograms. There is like a bunch of title involved in here, that the people need to create the planogram and physically execute it. And then, with the help of our mobile application that you're able to see in here, somehow they need to go through reporting parts, and they need to attach like a live picture, or they need to send a comment, and the back office, like the people that were created planogram originally, they will get the

report from the execution at the location, from the different stores, and they will be able to see the picture, they will be able to like compare the planograms, how it looks like to what it was originally for, and as well, it can it can be ended up like with a planogram analytics, and with the profound like BI blog that you will be able just to see in a few minutes. And what about analytics, Anna? Do you want to tell us a little bit more and show us just a few reports and I will stop sharing on this moment. Thank you guys. Yeah, so thank you Mark for giving some introduction and regarding giving the idea of who we are as a company. I'm not going to share like just a few reports. I'm going to share the total like BI part and we'll share in general regarding the analytic possibilities of the Leafio system. Why it is important like we think that first of all like the merchandising process, the planogram creation process,

it should be first of all about numbers. And that's why we are creating the solutions that allow not just like to conveniently draw the planogram, communicate it to the store, but to be to make this process the data-driven. So to make everything to help the company to reach their economic goals. Like increase the sales, to optimize the assortment, of course decrease human resources and other at the different KPIs that can be achieved with the help of the software. So that's why we think that analytics is very important in general. We use and we have very extensive blocks in all our modules that Mark shared and we focus a lot on that and during the implementation, during the customer support, we our people are always like analyzing the results of our potential our like existing clients and based on that they provide some recommendations to the

clients on like what can be improved. So with this being said, I I will share the I will share my screen and will tell you more, will give you the more the idea of like how analytic is structured in in our system. Of course like if you're interested in the merchandising process, if planogram is something that is not set up in your company, please feel free to contact us. We will be able We will be glad to arrange a special demo for you and showcase the whole process that in the system. But today it's not the topic of our discussion. We will focus just on the analytics part. So, in Lift system, there are several I would call it like layers of the analytics because it's important like first of all to do that on the macro space and level, to do it on the micro space and level of the planogram, and there's a separate BI part that allows like to to go into very small details to understand what are the issues in the

process of the merchandising. And of course, as a next step to make decision what can be improved. So, what we can see right now, we can see the macro space and part, we can see the floor plan. And regarding the analytics possibilities here, we have here the analytics part. And if we upload and choose some particular period of time, we can upload here different types of the analytics or different types of the reports like ABC by the selling price, ABC by net price, ABC by margin, sales by selling price, net price, margin, share sales, cost share, and share profit. So, a lot of like parameters that can be seen on the level of the floor plan. So, let's upload. We chose I will just remind that we chose the period of time for which to build the report and show us the analytics. And after that, we make it like available on the level of the floor plan. So, basically what we can see right now here is that the system highlighted for us

the equipment, the fixtures according to ABCD analysis. So, basically this is like the A performing equipment, this is the B performing equipment, this is the C performing equipment, and this is kind of like the equipment that either we don't have data for or uh that we like there are no sales basically for this period of time. So there is one type of the report. So net price margin are like pretty similar but focusing like on the net price and on the margin of course and also we have we can build here the heat map in order to understand like what are the hot areas on our floor plan. So where where is the majority of sales are generated from. So in order to further make decisions about where to place some certain like category, subcategory, item, maybe complementary goods and so on. So this gives us the understanding

where the customer spend like more the majority of their money. So this is regarding the first layer of the analytics on the level of the floor plan. If you are talking about like the next level we are talking about the level of the planogram and it's important of course like to to track in during some period of after like some time. For example, when we created the planogram published it in the stores the store made the execution they made the like organized the shelf and after like one week two weeks one month depending on the like how SKU is moving like if it's a slow mover top mover to understand what are the numbers. So what you can do here on the level of the planogram is we can also choose some period of time. Let's choose maybe some longer period of time and we can highlight the planogram on the on to show us it on the level of the ABCD analysis. So first of all like what's important here of course like

our solution it can create like the planogram can be created there either manually or automatically and in this case the system will place everything by the biggest sales numbers like first of all, but still there are can be like a lot of factors that can influence the process, some guidelines, some cooperation with the vendors and so on. So it's important to analyze the current planogram. So what we can see here that the planogram is highlighted according to ABCD analysis. So basically of course like the A category is the green one, the B category yellow one, the C category the red one and the D category the black one. It's important to to understand that like the majority of the assortment that is placed on the shelf, it of course belongs like to the A category. Still of course we we might have the B category, C category, even D category. For example, if we're talking about the juices, it can be different flavors. So we should still have it for the assortment on the shelf. Or maybe it's

requirement from our vendor to have these goods on the shelf. So there are like a lot of different parameters that can like explain us like why these D items is on on the shelf. But still like it's a can be also a sign for us. For example, if we like we see this D items and we see that they are not selling for some period of time, it's a sign for us to go to the suppliers and to go negotiate on some I don't know, maybe to put that not like on the top shelf, but to put that on the bottom or to to remove this item from our assortment. So analytics provides like this clear visibility and this clear visibility it allows like to make the further decisions and have the understanding like what to do with this planogram, with these numbers. Of course we can build this ABCD analysis by the net price margin by quantity. And the next report that I'm going to show is like the heat map, but on the level of the planogram. So, basically

what we can see here, we can see here the top sellers and like some dead items. Yeah, we can see like how the items are sold on the shelf. What are the best like best movers, what are the slow movers and so on. And based on that, of course, like further make decision, for example, maybe restructuring the shelf, maybe dividing or dedicating some less space for this subcategory or category and so on. Uh so, this is regarding like the regarding the analytics on the level of the planogram itself. Also, we have additional possibility of creating this like um And we have the analytic cube that can be opened and we can see here like different items. We can create this table according to our priority. Like we can select and make active activate or deactivate some of the items, for example, and so on. Also, we can make some grouping by manufacturer, for example, so that the system will highlight like for us like

where is each particular vendor. And after that, we can click here, for example, for some row to see the numbers and after that it will highlight us this item on the shelf. And vice versa, if we click here, the this item will be highlighted here on the in the table. This is regarding the analytics possibility inside like the main like functional part, like inside the macro spacing part, inside the micro spacing part. But in Alitho, there is like a separate BI block that allows in general to analyze everything that is connected with the merchandising process. So, here in this um in this separate part, we have like seven reports and we can drill down to each report. We can build like more specific reports. We can create different filters. So here we can play in a different ways with this report and

to just to understand first of all like the bottlenecks and secondly to understand like how it is possible to solve this bottlenecks. So what we can see it here, this is the like one of the financial reports is like for like analysis. So basically when we are comparing two different periods of time. So we are comparing something with something else. So here we can either like choose all of the stores or like select some particular store. For example, we can do like that and we will have the analytics like for like for a year about or like for several weeks for just one particular store. And here we have like there one parameter which can be stored, it can be analyzed like the supplier, the planogram, the item, brand, region, store format. Even if you're a big company and you have like different different stores of different formats like supermarkets, hypermarkets, C stores and so on. You can go to the

store format and analyze it by each particular format. And from the other side, we can see the performance. So we can see there what has changed in terms of the sales, in terms of the profit, sales in pieces, sales per meter, profit per meter and so on so forth. So basically we can create this report like how it is convenient for us to see this kind of information. By default and here we can choose the of course the period type. So we can analyze there like we can make the like for like in terms of like the weeks, the years, the quarters and the months. So basically what we can see here and by default the system is analyzing like the last period with the previous period of time. So we can see like the main period the 51st week and the previous period of the 50th week. But also, of course, on the level here, uh like on the level of the table, we can uh choose uh some like different weeks. We can choose the different periods of time. We

can choose like three uh periods of time and so on. Uh so basically, when we are choosing, for example, we can see that the numbers has changed and um we can see here the main KPIs in terms of the merchandising and that uh needs to be analyzed. Uh so basically, here we can see the uh dynamic, like what has changed in terms of the sales. So in this particular case, we can see that the sales increased on uh 37 million uh uh and uh in percentage, it is 14%, 14.1%. So it's pretty huge increase in comparison with the previous week. Uh and uh by the way, everything that is uh like highlighted here in the reporting part in green color, this is something that is like, of course, like positive for the company. Something that is highlighted with the red color, this is something like negative for the company. Uh we can see here the change in profit, change in sales in pieces, sales per meter, profit per meter, sales per

facing width, and so on so forth. Uh here also on the table, we can see uh the sales, it's the purple part, and the profit is the pink part. And we can see sales in pieces here, like the increase of the gray gray line. If we want to go into some uh more details, we can go to this part of the report. Uh so here, we should choose like the analysis section, and to do that on the level, for example, of the planogram. Of course, here we can uh always choose like the store. We can choose even some particular planogram. We can choose the store format. We can choose region, supplier, brand, and analyze it like in a very in very convenient way for us. All these reports, they can be uploaded to Excel file, and they will preserve the same like structure, the same formatting as it shown here. Uh so, what we can see is like in terms of like this reports, we can see the planograms, some particular planogram,

and what has changed in terms of this planogram for about the sales, about the profits, sales in pieces. So, all our main merchandising KPIs. And of course, what is convenient is that we can see everything filtered from the biggest one to the smallest one, and highlighted with the good changes, the good positive dynamic is highlighted with the green color. Uh so, if we are talking about uh the next report, this is the report regarding the assortment. So, we know that especially like in grocery retail, but in other retailers as well, there is like the high percentage of the assortment rotation. So, we need to control that. Uh we need to understand how like from the parts of the merchandising if we are talking, we need to understand how quickly we are implementing the changes uh of like the changes that are connected with the assortment rotation. For example, if we understood that

new items are listed in the assortment. By the way, as Mark mentioned, we have a separate module for the assortment performance, where the assortment metrics can be created, when the items can be new items can be listed, delisted, and the assortment metrics created for each particular store. And it is very convenient in this tool to manage that, and information goes directly here like in order like for making the planogram, for understanding what is the current assortment metrics for for store. Uh but basically, what uh returning back to this report, what we can see here, we can see here two main coefficients. Yeah, and uh these coefficients, the first one, it shows us what is the share of unplaced active items in the assortment matrix. So, basically those are the items that were recently added to the uh assortment matrix, and we understood that with the next data exchange that there are like, okay, they're new items, but the system tells you that uh but these items are not yet

in the level of the planogram. So, we should go ahead and place this item in the planogram. Uh, and it shows like the coefficient of like uh what is like the number of these items. Here we can see the uh specific number of this item. And vice versa, here we can see the uh share of placed non-active items. So, it means that we already deleted this item from the assortment matrix, but it is still in the planogram. So, basically it means that the uh store more like store managers, most probably they are substituting that with something else. Or there is uh uh there the worst scenario that there is some empty space on the shelf. Uh, also we can go here into more details even, and we can filter items without balances. So, it means that some of the items they are non-active, they are not in the assortment matrix, they have no balance. So, basically there is no no items in the stores, but they are still in the planogram. And vice versa,

we can uh filter item items with balances. So, it means that new items were we are delivered to the stores uh or to the distribution center, and but they are not yet on the level of the planogram. So, we should hurry up and go ahead and place this item in the planogram. Uh, so let's go to the next report. By the way, uh, if you have any questions, please feel free to to send us here in the chat. We will be able to either like answer them during the presentation or at the end of the presentation. So, regarding the next report, it's also very like interesting one. So, if we choose some period of time here, in our case we chose December. Uh, we can choose here this store, and we can either see like all planograms in the store. Uh, we can see either all the planograms in the store, or we can choose some particular planogram, equipment type,

supplier, brand, whatever. Uh, or we can choose the planogram uh, here. For example, if we uh, go like to to this planogram. What we can see in this planogram, and what we are analyzing here in case of this report. So, this report shows us uh, what was the service level that availability level of the goods that are placed in this planogram. I will explain in more details. Uh, so here for example, we can see uh, the items on the zero shelf, and we can see that there are service level, the availability level of these items it's 99%. Of course, it's good, no questions here. Uh, this first shelf is good as well, but if we are talking about the second shelf here, the availability we can see it here like zero. So, it means that the items that are placed on the second shelf, they are like they had no they have no stock balance on the level of the store. And here we can uh, see the

uh, planogram for example, that the availability level is 60%, and so 40% of the items they had like of of 40% of the time there was no no stock balance for these particular items. Of course, we can drill down here and uh, like identify some each particular item, see the item on each particular shelf, and so on. So, to understand the service level, the availability level of of every item. Uh this is I see that there is some question. Does this planogram Does this planogram matrix also applies to fruits and vegetables analytics? Uh yes, it applies like to all kinds of analytics, but in terms of like fruits and vegetables, we won't see the item-based analytics, obviously. So, we will see if we are talking about like just regular fruits, of course, there can be like some

Sorry, I don't know, like very expensive fruits that we can count like by numbers. But, if it's like apples, for example, and not in the package, but it's like the bulk product, we are assigning like the sales to some particular area, and we will be able to see them in the planogram as well. Uh yes, thank you for the question. Uh so, let's go to the next report. Uh the next report is going to be about the layout structure. So, when we need to understand what is the area covered by some particular some specific products, for example, some specific category. Uh so, we choose in our case like the item group or the first item group is food, and the second item group group is juices. And here we can see the planogram details, and we can make this report bigger.

And can see different details about the width of the each planogram in meters, in linear meters, about the average facing width, share in width, facing width, facing height, depth, stock, and so on. Some main parameters about each particular like category, subcategory, and so on. Uh the next report, it's very interesting one, and this is the report about uh the efficiency of our layout and how we can increase that. So, for example, we choose here some period of time. We choose which type of the return which is the the type of the return rate, uh the calculation, uh the store, and give me a second, please. And some particular planogram. In our case, it will be like the low alcohol, for example. Uh and after that, what we can see here is we can see the report regarding

the sales return rate. Uh so, basically, what it helps us to understand and to get the idea of Uh here we can see like different items. And uh here the gray part is the share of this item in width. So, how what is the percentage? What percentage this item occupies on the shelf, on some specific fixture. Uh in like uh meters, and uh and the purple part is the part that this item occupies in sales. So, basically, ideally, uh this sales return This is called sales return rate. It should be uh close like to one. So, in other words, that the share in width of this item should be almost the same as the share in sales. Uh but why would do we need this report to showcase us this like unbalanced items that, for example, occupy a lot of place on the shelf, but don't bring us any sales. Or the items that uh

bring us more sales, but they are not like presented a lot on the shelf. So, what we can do it here for example and can analyze here. So, if we're talking about like this beer for example, we can see that it share in width is 20 6 27 almost 27%, but it share in sales is 11%. So, if we see like we can decrease the number of facings, the number of SKUs of these items placed on the shelf. If we're talking about this item, it's like the opposite situation cuz we can see that here it's occupies like less than 1% on the shelf. So, probably there's like just one bottle and but it brings us like a lot of sales like 34% of sales. Yes. So, basically in this particular case, we should consider increasing the number of these items and increasing the number of facings for this particular item.

In case of this report, it like ideally all the items they should be like here in the middle. So, it means that that the sales return rate for this item is items is balanced and it's like okay, we don't need to make any changes. But here with the help of this report, we can highlight and we can see clearly the outsiders. So, here and here and here for example, we can see that specifically like these items, they bring us very good sales, but they almost are almost not presented on the shelf. So, they have like one play one piece or something like that. And vice versa like these items, they are especially like these two items, they are presented a lot on the shelf, but they don't bring us any sales. So, it's a sign for us to work on this like these items. Uh and here we have some specific recommendations from the system on how

how this number of facings can be increased or decreased. So, here we can see the numbers of facings which change recommendations. So, here for example, for this beer we need to increase the number of facings for 49 and for like this drink we have to decrease the number of facings for four. So, there is some specific recommendation from the system. Uh let's go to the next report and this report it allows us also to understand the sales rate the return rate, but to do it on the level of the category subcategory so different like we can choose here different analysis section. Uh in our case what we can see here and this is also like very important like for the category managers for example to analyze like the share of their category and the with the place occupied by this category. We can see here different categories like

food, beverages, non-food, DIY, toys, and so on. So, here we can clearly see in this report that the DIY part it occupies 61% on the shelf, but it's share in sales like very very small. It's less than 3%. So, it occupies a lot of space for us and this space can be used for some other items that can sell better that can sell better. Like in in case of the food for example. So, the food in this case occupies like 25% of the space, but it's share in sales is around like 80%. So, clearly of course this is like this very simple example. There are a lot of like other different parameters that should be included and analyzed before that. But it's kind of a sign for us to decrease the DIY category and to increase the food category presence on the space. And last report, this one is like pretty complicated and

we use it usually during the implementation phase. Because during the implementation, what we do is we choose some particular stores we choose some particular stores for the pilot and we choose some other similar stores that can be compared with. So to get to see the effect of the automatic planogram generation or like automatic merchandising process so on. So what we can see here, we can choose some particular stores and we can here see the search for the similar stores or we can see here the like comparison of like some particular stores. And what's important for us in this case is this report. So we can see that the pilot store the pilot the planogram in the pilot store, it generated for us plus 58,000 58 something thousand dollars or euros I don't know what's here. So it's basically the increase on 42 and

a half percent. So what it mean what it means. Here we have the calculation by dynamics. So here we have the basic store and here we have the store for comparison. So the basic store increased like on the basic store that is the store for example where we launched the planogram generation where we set up the merchandising process with the help of the system. So here we can see that this store the sales increased in this store on 74% and we can see in the store for comparison it increased on 31%. So the effect if we compare like both of stores increased in sales, but in they are similar. So, our store where we organized the space with the help of the solution, it increased more in sales. So, we have the dynamic on 42% and here we can see it in the in money. And here we can see like that in other different numbers like effect by

share in sales and their calculation by share. Uh so, basically, this is it regarding the analytics. So, just to wrap up what me and Mark told about is it's very important if you decide to set up your merchandising process, uh not of course just like to focus on the visual part, but to focus on the analytics first of all. So, everything should be data-driven and of course it's hard to do that without any system in place or if you have like the separate BI block that is not connected with the merchandising system, it's also not very convenient to analyze that. It is good when everything is combined, everything is combined with in one in one place, everything is combined like for very convenient view and so on. Uh so, if any questions are, please feel free to write us in the

chat. As we mentioned, we will be glad to communicate in more details and to give you more understanding of either like this particular block of the merchandising optimization or any other particular block. So, please feel free to write us and we will contact you and organize a specific meeting. Uh thank you very much for everyone to joining us for joining us. I'm pretty sure that after this meeting you after this webinar, you will receive the recording and you will be able like to see the recording as well if needed just to get back to some important information. Thank you Anna. Thank you guys. Anna, it was so informative and I hope our guests was able to enjoy it as well and yeah guys, feel free to contact us and we will send you the recording of our webinar. Thank you for participation and have a great rest of the day ahead of you. Thank you everyone. We will be glad to

see you during our next webinars and thank you for participating today. Have a good day. Bye-bye. Have a good one.