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Retail Buying

How we assisted a B2B client to understand how their client base actually did business with them and how they could grow their profitability. Case Study

BACKGROUND TO THE CHALLENGE THAT OUR CLIENT FACED.

Our client was supplying a portfolio of products and related services to B2B clients.

  • They wanted to increase the sales to and profitability of existing clients.
  • They also wished to make new clients more profitable. They aimed to achieve this by understanding how to be more relevant to new clients in terms of the products and services that they would focus on as they grew each new client relationship from initial sign-up.

They knew that the volume of products and services sold to larger client organizations would generally be higher than those sold to smaller client organizations. But, they were not convinced that the scope of products and services sold to larger organizations would necessarily be different to those of smaller organizations.

  • A complicating factor was that competing sales teams currently tended to provide additional products and services at discounted prices to large clients if they purchased large volumes of their particular product or service. This negatively affected the profit margins on large clients, especially when the cost of servicing these clients was taken into account.
  • A further complicating factor was that seasonal clients might make a large purchase on a once-off basis, and be regarded as a key client, and get the benefits accorded to a key client, but not make other purchases for the rest of the year.

The challenge was:

  • Understanding how clients were grouped when viewed from a volume sales perspective and from a profitability perspective. This would help to understand whether certain large clients should be regarded differently from what was the current practice. For instance, our client could use this knowledge to better manage the practice of volume discounting. Our client held the view that a profitability segmentation provided a useful view of reality – in other words, how clients were grouped based on a willingness to pay for varying groups of services. This was done whilst being aware of how large volume buyers contributed to covering the business’ monthly fixed costs.
  • Determining whether profitability-based behavioral segments could be linked back to usable B2B client profiles. This was to enable them to identify clients with similar profiles who were more profitable. This would provide them with guidance on where they might modify deals with existing clients in later years, upon contract renewal, to boost profitability. It was also to enable sales teams to make more appropriate service recommendations and pricing decisions to new clients at the start of a relationship.

HOW THEY MET THE CHALLENGE, AND THE ROLE THAT WE PLAYED TO HELP THEM DO THIS.

Client had already tried to analyze profitability data across their B2B client base. They had tried several forms of analyses but were not getting the insights that they required for a variety of reasons.

They had two fundamental issues:

  • Being able to create and profile behavioral segments on the basis of volume sales and profitability across their entire product and service portfolio to all their clients. Their current practice was to rank clients on the basis of volume sales and profitability, but not actual behavioral segments.
  • Being able to understand the role of seasonal buying behavior in their business and how this affected the volume discounts and service levels mistakenly given to certain clients.

We were able to assist them in three ways:

  • We applied our behavioral segmentation processes and were able to segment their data and provide them with a variety of insights from a volume sales and profitability perspective across their client base.
  • We also assisted them to profile each client and linked each client profile to their behavioral profile (i.e. the behavioral segment that it belonged to.) This enabled them to benchmark clients against one another using relatively complex profiles. This allowed them to determine whether clients with similar characteristics were in fact behaving the same way in terms of the profile of products and services purchased and the profitability that they delivered.
  • We helped them to better understand how their client base behaved on the basis of seasonality.

 

THE IMPACT THAT THIS SOLUTION HAD ON CLIENT’S BUSINESS.

Understanding how the clients that they sold their services to were in fact segmented on the basis of volume sales and their profitability.

This gave them an indication of the different groups of buying behavior that existed amongst the clients they sold to, on the basis of each product and service sold.

It also helped them to compare client behavior when viewed on the basis of volume sales versus profitability. In other words, it helped them to uncover client and sales team behavior that was harmful to their business.

This helped them to indentify potential challenges in the future when negotiating deals with clients.

Understanding how many clients belonged to each behavioral segment.

This gave them an indication of the maximum amount of clients they would be dealing with in each segment, should they wish to influence the buying behavior of clients within a specific segment.

This helped them to evaluate the resources required from a physical salesforce perspective versus other communications options.

Quantifying the value of each behavioral segment for each service in its portfolio.

With this information, they were able to identify the most profitable, least profitable and average profitability behavioral segment for each product and service within their portfolio. This then enabled them to ask further questions about whether the picture they were seeing for each segment could be improved.

Identifying unique characteristics of product and service profitability levels for each segment using the Index view.

This enabled them to identify where profitability of a particular product or service was particularly high or low in a segment, relative to other segments.

It also enabled them to identify what it was that made a segment unique in terms of its profitability profile, relative to the other segments. This led them to be able to ask questions, such as “Why are sales of this specific product or service in this segment so high? Are there common client characteristics that we could learn from and replicate elsewhere?” This also helped them to form an opinion on how new clients from a specific industry might be introduced to their product and service offerings over time. This would be done both from a salesforce perspective and a content marketing perspective.

Identifying the segments where unusually high or low levels of profitability were taking place, for each service, and using our Heat Maps that were provided to them at product or service level.

This enabled them to ask further questions. For instance, “Why are profitability levels so similar across all segments for a particular product even though the clients differ markedly in size and industry?” or “Why are profitability levels so high within that specific segment? What are the characteristics of that specific segment?”

Comparing clients with relatively similar profiles-such as location, industry, etc. in terms of the segment that each client belonged to.

This enabled them to identify clients that, in theory, were quite similar but were actually behaving differently in terms of profitability levels across the service portfolio.

By using this information, clients were identified that were deemed to have the potential to be more profitable, and the appropriate efforts were focused at those clients. Therefore efforts to amend the pricing of product and services of clients upon contract renewal, were based upon a reasonable likelihood of acceptance of the new volume pricing arrangement.

 

Investment_yes_no

How we assisted a client to invest their retail sales promotion budget more effectively. Case Study

BACKGROUND TO THE CHALLENGE THAT CLIENT FACED.

Client was supplying a portfolio of products to a national retailer with several hundred outlets.

They wanted to increase sales through these outlets, and continued to use a variety of in-store promotions, assisted by local advertising to do this.
They knew from past experience that a part of their promotional budget would be wasted as it would be applied to certain stores where it was probably not necessary, or was unlikely to make a difference.
In addition, certain stores would not have sufficient promotional assistance due to under-investment. In these cases, additional, focused promotional budget probably would make a difference.

They wished to remedy this situation by shifting their promotional investments, at store level, from where they were not necessary to where they were most needed.

The challenge was deciding on:

Which stores to allocate the promotional budget to.
Identifying the mix of products in their portfolio that the promotions in question would address in these stores, within each category.

HOW THEY MET THE CHALLENGE, AND THE ROLE THAT WE PLAYED TO HELP THEM DO THIS.

Client had already tried to analyze sales data for over 30 product types across several hundred stores.

They had tried a variety of analyses that were not delivering the insights that they required.
Additionally they recognized that sales within each store would be influenced by a variety of factors. These included the location of the store, the intensity of competition within the area where the store was located, the store format and the ability of management running the store – to name a few. This would have to be considered when allocating promotional budgets to each store.

They had two fundamental issues:

Being able to identify and picture store behavioral segments. This would be on the basis of sales volumes across their entire product portfolio across all stores. The view provided by their business intelligence system provided either too much data to make sense of, or too summarized a picture to provide insights. They decided that reordering the data into behavior-based segments would make more sense.
Being able to determine what a reasonable sales level for each product in the portfolio should be for a particular store type in a given competitive environment.

We were able to assist them in two ways:

We used their sales volume data for a specific period of time across their entire product portfolio at store level. We then applied our behavioral segmentation processes and were able to segment their data and provide them with a variety of insights.
We assisted them to profile each store and linked each store profile to its behavioral profile (i.e. the behavioral segment that it belonged to.) This enabled them to benchmark stores against one another using relatively complex profiles. This enabled them to make more informed judgements as to where sales promotion budgets should best be directed.

THE IMPACT THAT THIS SOLUTION HAD ON CLIENT’S BUSINESS.

Mapping & sizing store segments on the basis of their buying behavior across the product portfolio.

This gave them an indication of the different groups of buying behavior that existed amongst the stores they sold to, on the basis of volumes of each product sold. Hence, they got to be aware of the different types of buying behavior that existed.

They also got an indication of the maximum amount of stores they would be dealing with in each segment, should they wish to influence the buying behavior of stores within a specific segment.

Additionally, they were able to identify the best, worst and average selling stores within each behavioral segment for each product within their portfolio.

This enabled them to ask further questions about whether the picture they were seeing for each segment could be improved.

Profiling each segment’s unique characteristics.

This enabled them to identify what it was that made a segment unique in terms of its sales profile, relative to the other segments.

It also enabled them to identify where sales of a particular product were particularly high or low in a segment, relative to other segments.

This led them to be able to ask questions, such as “Why are sales of this specific product in this segment so high? Are there common store characteristics that we could learn from and replicate elsewhere?”

Identifying unusual behavior at product level within segments and across segments.

This enabled them to ask further questions…

For instance, “Why are sales volumes so similar across all segments for a particular product even though the stores differ markedly in size and location?” or
“Why are sales volumes so high within that specific segment? What are the characteristics of that specific segment?”

Aligning current store behavior with its potential behavior.

This enabled them to identify stores that in theory were quite similar but were actually behaving differently in terms of sales volumes across the product portfolio.

By using this information, stores were identified that were deemed to have the potential to do better.
Sales promotion efforts were customised and focused at those stores. Therefore promotional budgets were directed at stores where they were able to identify specific needs and a reasonable likelihood of improvement in sales.

Customer_Service

How we segmented retail sales data to persuade a retailer to buy more from their supplier. Case Study

BACKGROUND TO THE CHALLENGE THAT CLIENT FACED.

Client was supplying a range of products to a national retailer.

The retailer provided a variety of services to its customers and used client’s products in the process of providing these services.
The more that the retailer’s customers patronized the retailer, the more likely that client would get to sell a greater volume of their products through the retailer’s network.

Although client wanted to increase sales through these outlets, they realized that this would only happen if they could understand how customers bought services from the retailer. Once they had this understanding, they would be better placed to advise the retailer to implement the necessary changes to boost customer patronage.

Client had already established that the retailer tracked the behavior of each customer’s purchases with the assistance of a database.
They had also established that the retailer’s customers varied markedly in terms of spend, but could not understand why.

The challenge was to understand customer behavior through segmentation so that we could group customers with similar behavior.

Once this was done, we would be better able to understand and address the unique needs of each customer segment by understanding behavior rather than demographics only. Then they could drive behavioral change where necessary.

 

HOW THEY MET THE CHALLENGE, AND THE ROLE THAT WE PLAYED TO HELP THEM DO THIS.

Client had already tried to analyze sales data for their product portfolio across all of the retailer’s stores.

They had tried a variety of analyses that were not delivering the insights that they required.

They had two fundamental issues:

They could not understand why customers varied so markedly in terms of their spend.
They could not understand how different customers timed their visits to the retailer.

We were able to assist them in three ways:

We used behavioral segmentation to provide them with a variety of insights regarding how customers bought their products.
We also showed them how this related to customers’ timing of purchases.
We used behavioral segments to define separate research samples. Each sample was researched and demographics and motivations for purchasing were identified. These insights were used to craft communications and related strategies to enable specific segments to increase their purchases from the stores.

These insights were used to identify the make-up of each store’s customer base as it related to the usage of client’s products.

 

THE IMPACT THAT THIS SOLUTION HAD ON CLIENT’S BUSINESS.

Helping to understand why customers behaved the way that they did – and then to do something about it.

We were able to isolate the behavioral segments that customers fell into on the basis of their buying behavior from the stores.

Equally importantly, we were able to show how the time dimension of customer buying behavior affected the behavioral segmentation findings.

With this information, they were also able to identify the best, worst and average selling customer behavioral segment for each product within their portfolio.

Client was able to use our findings to guide research on the demographics and motivations behind each customer segment.

They discovered that customer demographics were a key basis for buying triggers and the frequency of visits to the retailer.
This then enabled them to ask further questions about whether the picture they were seeing for each segment could be improved. For instance, our index-based Profiler view of behavioral segments enabled them to identify what it was that made a segment unique in terms of its sales profile, relative to the other segments.

This led them to be able to ask questions, such as

“Why are sales of this specific product in this segment so high?
Are there common store characteristics that we could learn from and replicate elsewhere?”

They were also placed in a better position to determine how much to spend on retaining key customers, and how much to spend on changing customer behavior to move them to more profitable segments. They were then able to make recommendations to the retailer on individualized communications to each customer segment to change and / or maintain their buying behavior.

Understanding how the stores that they sold their product portfolio to were in fact profiled on the basis of their customers.

This gave them an indication of the different groups of customer buying behavior that existed amongst each store they sold to since store buying behavior was a function of the customers they sold to.

Client was better able to assist each store to understand if and why they could be attracting specific types of customer segments to their store that they were currently not attracting. This enabled them to enact store-level marketing initiatives for each store.

MakingDecisions

How we assisted a B2B client to understand how their client base actually did business with them and how they could grow their profitability. Case Study

BACKGROUND TO THE CHALLENGE THAT OUR CLIENT FACED.

Our client was supplying a portfolio of products and related services to B2B clients.

They wanted to increase the sales to and profitability of existing clients.
They also wished to make new clients more profitable. They aimed to achieve this by understanding how to be more relevant to new clients in terms of the products and services that they would focus on as they grew each new client relationship from initial sign-up.

They knew that the volume of products and services sold to larger client organizations would generally be higher than those sold to smaller client organizations. But, they were not convinced that the scope of products and services sold to larger organizations would necessarily be different to those of smaller organizations.

A complicating factor was that competing sales teams currently tended to provide additional products and services at discounted prices to large clients if they purchased large volumes of their particular product or service. This negatively affected the profit margins on large clients, especially when the cost of servicing these clients was taken into account.
A further complicating factor was that seasonal clients might make a large purchase on a once-off basis, and be regarded as a key client, and get the benefits accorded to a key client, but not make other purchases for the rest of the year.

The challenge was:

Understanding how clients were grouped when viewed from a volume sales perspective and from a profitability perspective. This would help to understand whether certain large clients should be regarded differently from what was the current practice. For instance, our client could use this knowledge to better manage the practice of volume discounting. Our client held the view that a profitability segmentation provided a useful view of reality – in other words, how clients were grouped based on a willingness to pay for varying groups of services. This was done whilst being aware of how large volume buyers contributed to covering the business’ monthly fixed costs.
Determining whether profitability-based behavioral segments could be linked back to usable B2B client profiles. This was to enable them to identify clients with similar profiles who were more profitable. This would provide them with guidance on where they might modify deals with existing clients in later years, upon contract renewal, to boost profitability. It was also to enable sales teams to make more appropriate service recommendations and pricing decisions to new clients at the start of a relationship.

 

HOW THEY MET THE CHALLENGE, AND THE ROLE THAT WE PLAYED TO HELP THEM DO THIS.

Client had already tried to analyze profitability data across their B2B client base. They had tried several forms of analyses but were not getting the insights that they required for a variety of reasons.

They had two fundamental issues:

Being able to create and profile behavioral segments on the basis of volume sales and profitability across their entire product and service portfolio to all their clients. Their current practice was to rank clients on the basis of volume sales and profitability, but not actual behavioral segments.
Being able to understand the role of seasonal buying behavior in their business and how this affected the volume discounts and service levels mistakenly given to certain clients.
We were able to assist them in three ways:

We applied our behavioral segmentation processes and were able to segment their data and provide them with a variety of insights from a volume sales and profitability perspective across their client base.
We also assisted them to profile each client and linked each client profile to their behavioral profile (i.e. the behavioral segment that it belonged to.) This enabled them to benchmark clients against one another using relatively complex profiles. This allowed them to determine whether clients with similar characteristics were in fact behaving the same way in terms of the profile of products and services purchased and the profitability that they delivered.
We helped them to better understand how their client base behaved on the basis of seasonality.

 

THE IMPACT THAT THIS SOLUTION HAD ON CLIENT’S BUSINESS.

Understanding how the clients that they sold their services to were in fact segmented on the basis of volume sales and their profitability.

This gave them an indication of the different groups of buying behavior that existed amongst the clients they sold to, on the basis of each product and service sold.

It also helped them to compare client behavior when viewed on the basis of volume sales versus profitability. In other words, it helped them to uncover client and sales team behavior that was harmful to their business.

This helped them to indentify potential challenges in the future when negotiating deals with clients.

Understanding how many clients belonged to each behavioral segment.

This gave them an indication of the maximum amount of clients they would be dealing with in each segment, should they wish to influence the buying behavior of clients within a specific segment.

This helped them to evaluate the resources required from a physical salesforce perspective versus other communications options.

Quantifying the value of each behavioral segment for each service in its portfolio.

With this information, they were able to identify the most profitable, least profitable and average profitability behavioral segment for each product and service within their portfolio. This then enabled them to ask further questions about whether the picture they were seeing for each segment could be improved.

Identifying unique characteristics of product and service profitability levels for each segment using the Index view.

This enabled them to identify where profitability of a particular product or service was particularly high or low in a segment, relative to other segments.

It also enabled them to identify what it was that made a segment unique in terms of its profitability profile, relative to the other segments. This led them to be able to ask questions, such as “Why are sales of this specific product or service in this segment so high? Are there common client characteristics that we could learn from and replicate elsewhere?” This also helped them to form an opinion on how new clients from a specific industry might be introduced to their product and service offerings over time. This would be done both from a salesforce perspective and a content marketing perspective.

Identifying the segments where unusually high or low levels of profitability were taking place, for each service, and using our Heat Maps that were provided to them at product or service level.

This enabled them to ask further questions. For instance, “Why are profitability levels so similar across all segments for a particular product even though the clients differ markedly in size and industry?” or “Why are profitability levels so high within that specific segment? What are the characteristics of that specific segment?”

Comparing clients with relatively similar profiles-such as location, industry, etc. in terms of the segment that each client belonged to.

This enabled them to identify clients that, in theory, were quite similar but were actually behaving differently in terms of profitability levels across the service portfolio.

By using this information, clients were identified that were deemed to have the potential to be more profitable, and the appropriate efforts were focused at those clients. Therefore efforts to amend the pricing of product and services of clients upon contract renewal, were based upon a reasonable likelihood of acceptance of the new volume pricing arrangement.

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