Category: CRM Experts

At a time of increasingly complex customer engagement, nothing is more important than building personas to support Retailer Marketing Strategies

Customers personas are archetypical Customers whose habits and characteristics represent the behaviors of a larger group of Customers. Usually, a persona is defined by both Shopping Patterns and Demographics.

With a proper persona strategy in place, the Marketing Team will be better prepared to engage customers in the appropriate channel with the appropriate commercial offering and message.

Building and using personas is pivotal in the deployment of the Personalization process (and must be carefully crafted to be fully compliant with each local Data Privacy Protection’s regulations)

As this case study demonstrates, each additional effort delivers measurable impacts.

Challenge

Our Client’s Marketing Team was aware of the importance of Personas and how its usage would support both sales and loyalty growth objectives. The challenges the team was facing were how to define these customer persona’s and translate them into data sets so each corresponding customers list (or segment) could be built. To do this, the Marketing Team had to go beyond the standard customer segmentations they were already using in their B2B and B2C sales channels.

Considering the importance of understanding those 2 components of CRM, it became a priority to redefine them and review the process to create activable customer personas.

Action

With the Client’s Marketing and CRM Team firstly, we review the difference between Customers segments and Customer persona.

Customer segment is a group of Customer based on common characteristics such as their spending or purchasing behaviors.  

For example, “Our main Customers are women aged 35-50”. It can be seen that this information is targeting a group but in fact if we imagine a “35-year-old woman living in a condominium in a megalopolis” and a “50-year-old woman living on the countryside” the digital marketing approach to reach these two shouldn’t be the same and it’s where Customer persona takes all its necessity.

Personas are fictional representations of segments of buyers based on real data reflecting their behaviors when they shop Essentially, they help understand the customer base in a way that is meaningful and will drive personalization relevance.  

Building on this clarification, the Team decided to review how they create their Customer Persona and what type of engagement they could then implement.

They did this in 4 steps.

Step 1: Setting up the Persona

The started by creating 4 personas (1)

• “Health Focused” they identified Customers for whom the share of wallet for Fresh Products in their basket was above 20% with the highest purchase frequency in these categories, they even go further by creating a persona “Vegetarian” and identified Customers who bought only vegetables and Soya based products”.

• “Wise Savers” they identified Customers for whom the share of wallet of promotion above 40% in their top 15 categories

• “Saving Students”, they considered customers below 22 years old as students.

• “Good Parents”, they identified their Top Customers having Baby Diapers and Baby Food in their basket with the highest frequency of purchase in these categories.

Step 2: Persona Segmentation

After identifying customers as per the persona’s criteria, they sub-segmented those personas according to the Customers spending (basket value / Average value by item). The Team registered these sub-segments would be used later for targeted campaigns and personalised offer.

Step 3: Setting Up the Business Rules

For each Persona segment the Team used cross-merchandising function into their CRM Tool to identify Persona-Centric Engagement Drivers:

• Automation: for which new products customers should be informed, what type of incentive to be proposed for 1^st purchase and at what frequency  

• Deals: What recurring offer could be sent (like weekly deals, monthly grabs, etc…) with what mechanics
• Campaigns:  What products focused campaigns (like a mini catalogue) could be built by persona, at what frequency and with which offer structure

While the Automation part was rather easy to implement, the Promotion Campaign still required recurring cross-merchandising reviews to ensure the commercial offer was reflecting passed purchase behaviors.

Step 4: Execution & Fine Tuning

Because Customers groups are permanently evolving, the execution phases quickly showed that a tight monitoring (and several tests) were required to fine-tune both the business rules (if we accept to have a Customer in several persona, what are the risks of overloading them with too much offers – even if personalised?)  as well as the various components of the Engagement drivers, from product selection to mechanics, media and frequency.

Results

After 4 Months Customers which were part of Customers Persona segment program had:

• a 20% higher purchase rate on new products
• a visit frequency increase from 3,1 to 3,6 times per month (+16%)
• Persona related customers’ basket grew 3% more than other loyal shoppers

To maintain these gains, in addition to the Engagement Drivers performance reviews, the Team decided to review the accuracy of their Persona Customer List quarterly. The main reasons behind these decisions are:

• Ensure new customers fitting the persona are included, other slipping out of the persona to be excluded from the List
• Fine tune each person’s selection criteria
• Ensure the shop is talking to their customers the way they want to be spoken to, so they will pay attention to what they are saying (Activities, Offers, Promotion)

What does this show?

Customer personas provide tremendous value and insights to improve the Loyal Customer experience by:

• Improving Assortment
• Providing guidance to Marketing Team on their Targeted Commercial Offer
• Increase Promotions & Campaigns’ return on investment.

On our side, we were of course happy to see that our CRM Experience and our CRM solution for retailers, Ulys(*) and, was helping create the right value to our client and help strengthen their Loyal Customers experience.

About the authors

Frederic Klein is Retail Director at Hypertrade. With over 20 years of retail experience across 4 continents, Frederic helps Clients to implement our solutions, train and coach CRM’s Team.

Nitikon Manchanda (Mikey) is a Consultant at Hypertrade. With his deep knowledge in CRM, Mikey supports Clients to define the best parameters for their CRM Solution, helps CRM Team in their Customers analysis and provide them recommendations to improve Customer’s experience.

(*) Ulys Customer Intelligence SaaS Software is a proprietary Shopper Analytics that helps retailers measure, understand, and engage Shoppers. 

Contact us to learn more how Ulys Customer Intelligence SaaS Software can help you improve your campaign efficiency.

The rise of CRM as a critical component to the Customer Experience is accelerating. As Customer Service in the past, the quality of retailers ‘Loyalty Programs has become one of the unavoidable criteria Customers use to evaluate their preferred shops. Looking at the financial weight of loyalty – from sales and margin contribution to rising customers’ acquisition costs – retailers are now paying a serious attention to the CRM experience they are proposing to their Loyal Shoppers. As this case study demonstrates, each additional effort can have measurable impacts.

Challenge

Our Client’s Loyalty sales’ contribution were slowly but regularly sliding down, while non-loyalty sales were displaying an aggressive growth, boosted by the post-Covid period. The Team has challenges identifying the causes at the origin of this progressive decline. Taking into account the importance of Loyalty Sales in terms of basket size, shopping frequency and margin contribution, it had become a priority to identify the causes and find their remedy

Action

With the Client’s Marketing and CRM Team, we started a simple approach to do some measurements to identify in which areas the pains were located. Some of the first interesting measurements was that the Loyalty sales decline was not impacting customers whose Loyalty was over 24 months old. While there were no outstanding growth trends in their purchase behaviors, there was rather a level of steadiness. But these numbers changed drastically when we started to focus on new members, despite the regular recruitment campaigns they were running both online and in their stores.

2 indicators were in the red:
 
· The time between the first purchase and the second purchase of new members
· The evolution of the shopping frequency (both online and online) of newly recruited members

Building on these numbers, the Team realized that there was no established on boardingfor new customers. In case some major Loyalty events were taking place right after new customers’ enrolment, these new customers were happy. And not happy if nothing was happening. With the Marketing and CRM Teams, we started to build a simple onboarding program, whose steps frequencies were articulated on the shopping behaviors we identified. Our client therefore has decided to take a few standardized actions to improve their New Loyal Customer Experience

Great: a simple sThank you message for becoming a member. In our case, the client decided to adda purchase coupon as a sign of gratitude.

Recognize: another Thank you note for the 1^st shopping trip after enrollment, along with a program of the upcoming events

Investigate: In case the newly enrolled customers didn’t have any purchase after 2 standard buying cycle, a note with a question about potential challenges, a hotline number

Keep in touch: sending regular emails to their existing Loyal Customers, letting them know about new products, upcoming promotions, or special offers.

Learning More: what products Loyal Customers have purchased or not purchased. This information help to know what Loyal Customers want and what additional products they might be interested in. Our Client can better tailor an offer on a product and organize Targeted Campaign. Personalized service can improve customer satisfaction and increase their Retailer brand loyalty.

Results

After 3 Months
· New enrolled Customers reduced by 21 Days the frequency between their first purchase and their second purchase.
· Existing Loyal Customers increased their number of visits to 3.5 times per month (+18%) and spend on average + 25%
· Overall Total Loyalty Sales increased by18%

To keep this very positive trend through better Customer experience, our client ensured that their Loyal Customers would receive a special offer linked to their purchase behaviors every 30 days.

What does this show?

There is no perfect Onboarding program, and the important point is to have one, firmly established and executed. The ROI of such a policy is based on several factors:

· Emotional: customers feel recognized and valued instead of ignored
· Financial: it accelerates the following sales and impact Customer Lifetime Value
· Commercial: each step of the funnel can be measured and improved

On our side, we were of course happy to see that our CRM solution for retailers, Ulys(*), was helping create the right value to our client and help strengthen their Loyal Customers experience.

(*) Ulys Customer Intelligence SaaS Software is a proprietary Shopper Analytics that helps retailers measure, understand, and engage Shoppers.
Contact us to learn more how Ulys Customer Intelligence SaaS Software can help you improve your campaign efficiency.  

Have you ever run a first wave product campaign that was not successful? Most companies have

 However, most research shows the conversation rate of the 2nd and 3rd wave of any campaigns count more than the first.  

If the achieved conversion rate is not as high as expected, it doesn’t mean your campaign failed. It only means the assumptions about Customer Knowledge need to be sharpened. And this where post campaign analysis is critical.

Challenge

Imagine a retailer who notices that a specific category, which is supposed to be offering daily routine products, had a low and continuous penetration rate.

After having checked prices, assortment and quality, the retailer deduces that there may be reputation challenges that are preventing shoppers from buying.

Action

The retailer therefore decides to identify all shoppers who never shopped in this category and send them an attractive proposition and measures the impact.

Results

• At first, the retailer’s teams were disappointed: only 6% of the contacted shoppers took up the offer. So they decided to separate this initial target group by two, and analyze  their post campaign behavior: Group 1  Those who did not respond at all.
• Group 2 These who converted the offer in a purchase

1^st  Analysis 

For those who did not respond, they decided to send the same campaign every week for the following month each time at a different time of the week. By doing so, they identified what day was relevant to each shopper.

The impact was growing their conversion rate by another 8%.

2^nd  Analysis

For those who responded positively, the company analyzed the customers’ other purchases in this category.  Surprisingly, they found 30% continued shopping in this category.   

To drive better engagement, the company ensured that these loyal shoppers would receive an offer adapted to their basket value every 30 days.

The overall here was they   gained an additional 25% shoppers from out of the second ‘converted’ group

What does this show? Some campaigns are more important than others.

‍The strategic ones only end once a real learning (and measurable conversion) happens.  

‍Contact us to learn more how Ulys Customer Intelligence SaaS Softwarecan help you improve your campaign efficiency.

‍Ulys Customer Intelligence SaaS Software is a proprietary Shopper Analytics that helps retailers measure, understand, and engage Shoppers. 

One can easily find CRM glossaries online, and some of them are really good. Still, we could not find a glossary that is specific to retail and that could explain the practical usage of the main components of CRM for our own growing Teams.

So, we decided to build our own. If we are lucky, our little efforts will also be useful to others

Ulys Customer Intelligence SaaS Software ™ is a Retail CRM online Solution published by HPT Ariane Ltd, South East Asia Leading Retail Collaboration Platform.

Fed by POS Data, ERP and CRM Data, Ulys Customer Intelligence SaaS Software ™ is a tool that enable retailers and marketers to understand customers purchase and non-purchase decisions.

Developed by and for retailers, Ulys Customer Intelligence SaaS Software ™ is both offering simplicity in its usage as well as a really deep level or granularity.

Ulys Customer Intelligence SaaS Software ™ is articulated around functionalities:

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• CRM Performances & Profitability Dashboards
• Purchase behaviour
• Basket Analyses
• Purchase Trends
• Customer Segmentation
• Promotions
• Customers history

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Like many companies, our CRM activity is growing fast. Retailers are in high demand of improved CRM solutions and advanced Analytics. So, our Teams working on the development of our CRM Tools, as well as our Teams commercializing these solutions, are growing too. To welcome these newcomers, who might not always have an extensive experience of Retail CRM, we started looking for CRM Training Materials, especially glossaries, online.

One can easily find CRM glossaries online, and some of them are really good. Still, we could not find a glossary that is specific to retail and that could explain the practical usage of the main components of CRM. So, we decided to build our own. If we are lucky, our little efforts will also be useful to others.

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Part 1: Customers

Loyal Customers

Is a customer who owns a Loyalty Card – physical or Digital from her preferred Shop. Loyal Customers are often referred to as carded customers, in reference to the loyalty card they own.

Active Customers

Is a Customer that shops at a certain frequency, defined by the retailer. For example, if that frequency level is defined at least one shopping trip every 4 weeks over a period of, say 12 months, every customer that correspond to that pattern (shop at least 1 time every 4 weeks during a period of 12 months) is considered active.

A Customer who shops below a defined threshold of this pattern will be considered as inactive.

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New Customer

A new customer is a customer who recently acquired the card. Each company will define its own duration during which a Customer can be labelled as New.

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New Customer Onboarding Journey

Defines the several steps a customer will go through from the first interaction with the Loyalty Program (information quality, simplicity and easiness of access), then the registration itself, and the several interaction the retailer will have with her during the first weeks of her experience as a new member of the Loyalty Program Community.

Note: this is a Retail CRM area which is often forgotten by retailers, although it might be one of the most important components of any CRM Strategy. Let’s remember that there is the word Relationship in CRM. And like for all relationships, a good start can promise a great future

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Basket

Defines what carded customers buy during a shopping trip, online or in physical stores.

Share Of Wallet (SOW)

Defines the percentage of expenses of a group of products compared to the total basket value. Imagine a Customer spends 10 USD in her store visit. In these 10 USD, 2.75 USD have been spent on toothpaste and toothbrushes. The Oral Care share of Wallet of that customer in that shopping trip is then 27.5%.

The SOW can also be used to measure the customer behavior towards an activity

Imagine you run a promo for a Shampoo valued at 3.9 USD. If the Shampoo SOW is 95%, it means that the shopper came to your store to buy this promo only, indicating that no additional purchase has been generated from the promo.

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Housewife Basket (HWB)

Details and rank the products which are the most found in the baskets of Customers. The products that are the most frequently found in the Housewife Basket are therefore the products with the highest penetration rate (see Basket Penetration)

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Customer Lifetime Value (CLV)

CLV defines the value a customer will deliver to the retailer during her lifetime, either form a cashflow perspective (sales) or profitably (margin) perspective.

There are several ways of calculating CLV, and one of the most detailed and well explained approaches can be found in this article from Maryna Sharapa.

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Part 2: Behaviors

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The behaviors we want to focus on here only concerns what happens once the Customer is in the store (physical or digital)

Frequency

Is the number of times a customer shops within a certain time period

Recency

How recently a customer has made a purchase

RFM [Recency-Frequency-Monetary]

RFM analysis numerically ranks a customer in each of these three categories, generally on a scale of 1 to 5 (the higher the number, the better the result). The “best” customer would receive a top score in every category.

ABC Analysis

ABC analysis is a method of analysis that divides the subject up into three categories: A, B and C. It uses the Pareto principles and enables to group customers from the most valuable (A segment) to the least valuable (C segment)

COHORT Analysis

A cohort is a group of people with similar behaviors or characteristics within a certain period of time. Cohort analysis is a type of behavioral analytics, which is primarily identified by breaking down customers into related groups in order to gain a better understanding of their behaviors

Drop From Market

Is a market research term that defines customers who used to buy from a (set of) categori(es) during a certain period of time and then stopped.

New To Market

Is a market research term that defines customers who did not buy from a (set of) categori(es) during a certain period of time and then started.

Switch Gain

Defines, for a Brand, a group of customers who used to buy competitors’ Brands and then switched to their own Brands.

Switch Loss

Defines, for a Brand, a group of customers who used to buy their brand and then switched to their competitors’ Brands.

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Part 3: Customer Engagement

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Loyalty Program

A loyalty program is a marketing strategy designed to encourage customers to continue to shop at or use the services of a business associated with the program. It is usually embodied by a system of Card, physical or digital, which enables Customers to both accumulate and redeem points – or any other internal currency – as they shop.

Over time, Loyalty Programs have evolved from a Points Bank positioning to a promotion factory as well as active Communities where several benefits and advantages – involving 3rd  and related parties – are offered to its members.

The major ongoing trends in Loyalty Programs are:

• Increase of the Customer Centric-Evolution
• Review the Financial and Economics Models of Loyalty Programs
• Presence in various eco-systems and marketplaces
• Increased convergence with payments and Touch-Free
• Data Security
• Ever evolving member expectations

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Conversion Rate

Defines the number of customers who used a coupon or other received promotional mechanisms compared to the total number of Customers who received it

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Campaign

A campaign is a set of special offers proposed to customers over a period of time. Campaigns can serve several purposes and focus on various targeted members or future members

• Recruitment campaigns to invite new members
• Activation campaign, to stimulated specific member
• Promotion Campaigns
• Private Label Campaigns
• CSR Campaigns
• …

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Campaign Management

Is the ability to plan and monitor the several steps of a campaigns to maximise its efficacy and effectiveness. If we compare a Campaign Life Cycle to a Product Life Cycle, specific messages and stimuli will be needed at various stages of the Campaign’s life

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Onboarding Journey

Defines the several steps (the Experience) a new member will go through from right after her becoming a member to a certain period in time after the recruitment. It is useful to define these steps as well as setting objectives to the Onboarding Journey.

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Churn Rate

The churn rate, also known as the rate of attrition or customer churn, is the rate at which customers stop doing business with an entity. It is often as the percentage of service subscribers who discontinue their subscriptions – de facto or by stopping their shopping – within a given time period.

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Churn Management

Every time a customer leaves the program is a great opportunity to learn what happened. Churn Management consists of 4 key points:

• Understand why Customers leave
• Identify Customers most at risk to leave
• Identify among these customers who are the one we want to keep based on the value they bring
• Setup strategies to keep them

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Targeted Offer

A targeted offer is a commercial proposition sent to a specific customer based on her shopping preferences and behaviors.

• A targeted offer can be part of a campaign and is anyway managed like a campaign
• A targeted offer can be initiated and financed by the retailer.
• A targeted offer can be initiated by the retailer and sponsored by supplies

By definition, the Targeted offer is personalised.

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Part 4: Thoughts on CRM

Initially designed as a Point issuing Bank, CRM has evolved into a sophisticated tool to retain customers.

Technology now enables CRM program Managers to do much more than issuing points: they can create communities, be present in several eco-systems, enlarge the markets for the value of their own internal currency (the Point), understand shopper behaviors and directly interact with them with an adapted offer (i.e. Range, Assortment, Price and Promotion)

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Towards a new revenue management system for retailers

During the Pandemic, in locked-down and economically shattered environments, several retailers realised that their bottom line, despite the huge increase of operating costs and potential cash-flow challenges – was not that bad. One of the key reasons is that they had to drastically decrease their promotion and communications.

Still, even as retailers could not publish as many promotions as in the past, most of them successfully maintained suppliers support.

Still, It is probable that it might take some time before the return to massive promotion communication strategies.

Consequently, retailers will have to find new ways of generating additional income from suppliers to compensate the decrease in Promotion Support fees.

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The alternative and the big risk

CRM and its ability to build personalised and targeted offers is one of the most attractive alternatives for both physical and digital commerce. Such offers will be more efficient, and their generation of additional traffic and spending will by far surpass, at the member level, the results of previous mass promotions.

At the same time, customers level of satisfaction will also grow since the offer they will receive will be truly relevant to their needs and aspirations. And the fees income will be much greater, by product, than these generated through mass promotion communication.

The big risk for retailers and marketers is to over-exploit the direct and personalised engagement opportunities technology offers today. New business rules will have to be established to ensure that the retailers don’t become another nuisance on the Customer’s mobile phone or email inbox.

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CRM Management needs a re-think

At the very beginning of CRM, the CRM Manager was essentially a Finance expert: she was managing points, evaluating their impact of the margin and balance sheet. Her work and analyses were driving the financial value of the point and the redeem strategies.

CRM Management is today at a stage when CRM Managers have developed advanced analytical skills to understand shoppers, adapt their commercial offer accordingly, and build strategies: traffic pull, spending push and retention.

Today, CRM Teams face a new challenge: address what customers want more than money. Most researches on the subject agree that what matters most for customers is a collaborative relationship where consideration is the highest value currency. “Can’t buy me Love” as the song goes.

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In other words, it means that CRM Teams need to find ways to entertain personal relationships with millions of individuals simultaneously. Emotions are as important as transactions.

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Yes, of course technology will help. But technology will only help automate a set of business rules and communication engagement that Teams will setup (and yes again: Machine Learning will help optimise them).

So the paradigm-shift is here: the future of CRM and Customer engagement needs to accelerate its migration from “Mostly Transactional” to “Emotional and Transactional”.

In practice, it means that CRM Teams will have to change some of the usually asked questions like “How much should we invest / Finance” in such or such customer scenario into “What Question Should we ask?” or “What would be the best thing to say?”

From an operational perspective, it implies that Teams will have to setup new workflows, new metrics and new rules to address all the non-transactional aspects of the relationship and remain consistent with the Retailer’s vision on the omni-channel Customer Experience it wants to offer.