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Manthan Systems – Loyalty Management

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sponsored by produced by ® RIS News Custom Research Effective loyalty management needs to shift from being an underutilized resource to becoming a force for driving engagement and growth THE POWER OF EMOTIONAL CONNECTIONS
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Page 1: Manthan Systems – Loyalty Management

sponsored byproduced by ®

RIS News Custom Research

Effective loyalty management needs to shift from being an underutilized resource to becoming a force for driving engagement and growth

The Power of emoTional ConneCTions

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Page 2: Manthan Systems – Loyalty Management

Custom Research

R I S N E W S . C O M M AY 2 0 1 3 2

Loyalty is a complex, emotional connection that occurs be-tween a shopper and a brand. It is built over time through a combination of drivers. These drivers include marketing, mer-chandising, pricing, product mix, product satisfaction, shop-ping experiences online and in stores, problem solving when necessary, and positive interactions with associates. No single strategy or execution plan produces the number of loyal shop-pers required to support a retail business. Instead, an aggrega-tion of efforts is needed to build loyalty, and this makes it a challenge for retailers to manage and optimize.

Interestingly, not all retailers view loyalty as an essential discipline within the enterprise. Apple and Walmart, for ex-ample, do not have loyalty programs. But as the popularity of loyalty programs increases – the average American household

is enrolled in 18 loyalty programs – most retailers now view the tools used to manage a customer loyalty program to be a valuable resource.

However, there is a disconnect between customer and re-tailer perceptions of loyalty programs. At a basic level, a loyalty program creates unique customer profiles that enable track-ing of purchases. In many cases, purchases are converted into points and awards (although not all membership programs of-fer rewards based on points).

In all cases, however, the information collected in loyal-ty databases is intended to be a resource for marketing and promotional campaigns. But the operative word here is “In-tended.”

The truth is that retailers frequently underutilize their loy-

By Joe Skorupa

Effective loyalty management needs to shift from being an underutilized resource to becoming a force for driving engagement and growth

The Power of emoTional ConneCTions

Getting Personal with AnalyticsIt all started in the store with a customer. Then one customer turned into many customers. Then the store transformed into a channel in a world of multiple channels (mobile, social) where the face of your customer became murky due to drowning in the sheer volume of marketing data. Sound familiar?

Your customer doesn’t care if you can’t handle the Big Data tidal wave. They are too busy wading through the thousands of daily marketing messages received via social, mobile, e-mail, broadcast and print. Your lifeboat: Manthan’s Customer360 solution. Leveraging sophisticated but intuitive analytics solutions converts Big Data into a manageable current you can ride to shore – a place were you truly understand your individual customer across the sea of multiple channels.

Understanding your customer is merely the first step in the process. The following step adds more complexity to the mix, that is, the delivery of personalized, relevant communications

and offers to your customer base. Enter Manthan’s TargetOne solution: the ability to connect the dots between customer insights and customer communications. Revenue targets? It’s all smooth sailing when you can deliver 1-to-1 marketing to your target customers using desired communications vehicles such as e-mail, SMS, mobile apps or social media.

It’s time to get personal. It’s time to be personalized. Get on board with Manthan.

For more information on Manthan Business Intelligence solutions, please visit www.manthansystems.com.

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Page 3: Manthan Systems – Loyalty Management

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Custom ResearchCustom Researchsponsored by

What are your current analytics capabilities?

How well do you know the purchase history of your loyal customers?

F I G U R E 2

F I G U R E 1

R I S N E W S . C O M M AY 2 0 1 3 3

sophisticated group is split into two distinc-tive categories – 31.3% who say their capa-bilities are “good” because they allow some management of customer data and 25% who say their capabilities are “advanced” enough to enable delivery of personalized communi-cations and offers.

The remainder of the respondent pool ei-ther has limited customer analytical capabili-ties or none at all, which parallels the laggard group we saw in the previous question.

A theme is emerging in the study so far that indicates the ability to aggregate data across all channels, update it frequently, and then break it into key segments is a pathway to success pursued by retail leaders. This ad-

version rates for marketing campaigns.But before moving up to this advanced lev-

el, retailers need to aggregate data across all channels, frequently update it, and then break it into key customer segments. About half of retailers do not effectively do this today.

This insight raises a fundamental ques-tion about what retailers can actually do with data they collect. When we asked respondents to self-assess their customer analytics capa-bilities we find that more than half say they have good or advanced abilities. (See figure 2.) This is roughly the same number who said they have the prerequisites in place and are therefore ready to add more sophistication.

When we dig a little deeper, we find this

alty program capabilities and databases. One reason is the absence of an effective loyalty management and communication tool. Oth-er reasons include dispersed databases that make it difficult to synch up customer profiles and purchase histories, often due to a scatter-ing of responsibilities across multiple depart-ments using multiple IT systems.

Without effective tools and strategies to foster engagement, loyalty program members are no more loyal to retailers than other cus-tomers. The following datapoints from this month’s custom research study paint a clear picture of how savvy retailers are transitioning to a new level of customer engagement and a more profitable connection to shoppers.

Loyalty Glass Is Half FullA little over half of retailers (56.3%) either up-date loyalty data frequently and break it into segments and profiles or they collect aggregat-ed customer data across all channels (53.1%). These are the prerequisites for making effec-tive use of a loyalty program. The takeaway is that nearly half of retailers cannot effectively grow and foster their loyal customer base. (See Figure 1.)

This is a surprising finding considering the potential for growth retailers can tap by engaging profitable customers. In the loyalty laggard group are the 25% who say they do not collect individual customer data. Mem-bers in this group either do not believe their niche is well suited to loyalty marketing or in-stead believe their efforts are better focused on other strategies, such as everyday low pric-es, for example.

Interestingly, we see evidence of an emerg-ing sophistication among loyalty program leaders in this chart – 25% say their loyalty purchase histories are augmented with opt-in personal information and another 15.6% say their customer purchase histories are aug-mented with social graph information.

Adding personal details and preferences like these to customer profiles increases the ability of loyalty marketers to deliver more relevant communication to customers and sharpen personalized offers to improve con-

Data is frequently updated and broken into segments/profiles

Collect aggregated customer data across all channels

Individual customer purchase data not collected

Customer purchase history is augmented with opt-in personal information

Customer purchase history is augmented with social graph information

56.3%

53.1%

25%

25%

15.6%

Decent, generatingbasic reports

Good, allowing managementof customer data and

customer segments

Advanced, enabling delivery of personalizedcommunications and offers

None, currentlyresearching options

31.3%

15.6% 28.1%

25%

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Page 4: Manthan Systems – Loyalty Management

R I S N E W S . C O M M AY 2 0 1 3 4

What are you doing with your customer and loyalty data?

What type of solution(s) does your company use to manage loyalty marketing functions and services?

F I G U R E 4

F I G U R E 3

which is currently being used by 32.3% of re-spondents. If a retailer already knows what an individual customer or group has purchased, the next step is to send a relevant offer. It could take the form of a discount for purchase of cell phone accessories sent to recent pur-chasers of cell phones. Or it could be a cou-pon for lawn furniture sent to recent purchas-ers of lawn mowers. Targeted offers like these resonate with shoppers and are not viewed as clutter or spam, thereby often achieving a higher conversion rate than mass campaigns.

Other options found on this chart follow a pattern seen previously in the study – the more advanced the technique is the fewer retailers we find deploying it. Since loyal

What Do You Do with the Data?Regardless of the type of technology retailers have we wanted to find out what loyalty mar-keting techniques they most frequently use to drive sales. Not surprisingly, the top tech-nique is delivering targeted offers and com-munications to specific customer segments (48.4%). This is closely followed by tracking/managing points and rewards for historical analysis (41.9%). These are table stakes in loyalty marketing, which means they are nec-essary first steps on the maturity ladder. (See Figure 4.)

A more advanced technique is analyzing purchases to drive cross-selling opportunities,

vantage is leveraged by smart executives who use marketing tools to design and execute highly relevant promotion campaigns.

Loyalty Program ToolsEven retailers that do not have purpose-built loyalty software possess some type of technol-ogy that enables them to help shape a strategy to encourage frequent shopping by their best customers. At least most do. (See Figure 3.)

The largest segment of these retailers uses custom software that is built in-house (46.9%). The second largest segment uses a packaged CRM solution (28.1%) and the next largest group uses third-party outsourced ser-vices.

Interestingly, only 9.4% of retailers use a packaged loyalty solution, which is one of the major findings in the study because it speaks volumes about the retail industry’s assess-ment of currently available software. Clearly, if packaged loyalty software had evolved into proven solutions many retailers would use them. Instead, nine out of 10 retailers say they do not.

Anecdotal evidence indicates that some re-tailers base their negative perception on loy-alty software from past experience with CRM solutions, which were not purpose-built for the retail business model. Instead they were typically broad-based business analytics tools built for application across multiple indus-tries. Many experienced retail technologists refer to applications of this type as little more than tool kits requiring assembly. Attempts to adapt broad-based CRM tools like these to the requirements of retail have a history of producing questionable results at high cost.

Since retailers prefer to sell products to shoppers rather than write software code, there is a significant opportunity awaiting software vendors to demonstrate clear value, measurable performance gains, higher sales, greater purchase frequency, bigger wallet share, better conversions and other improve-ments in key performance indicators. Nine out of 10 retailers would likely open their doors to vendors like these.

Custom software built in-house

Packaged CRM solution

Third-party outsourced services

None

Packaged loyalty solution

Data sharing with suppliers for customer analysis

46.9%

28.1%

9.4%

18.8%

25%

3.1%

Delivering targeted offers and communications to specific segments

Tracking for historical analysis and points/rewards program management

Analyzing purchases to drive cross-selling opportunities

Setting sales targets and forecasts

Nothing, do not strategically use customer or loyalty data

Creating tests in micro segments

Performing predictive analysis to improve forecasting accuracy

41.9%

32.3%

29%

19.4%

16.1%

16.1%

48.4%

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Custom Research

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Page 5: Manthan Systems – Loyalty Management

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Custom Research

R I S N E W S . C O M M AY 2 0 1 3 5

What obstacles need to be overcome in your organization to effectively use loyalty data and a loyalty solution?

Where are you planning to invest within loyalty marketing?

F I G U R E 6

F I G U R E 5

program refers to building a strategy and then developing an execution plan for a rewards/points program or for a non-points program that offers instant discounts or surprises at checkout (like Panera Bread). Regardless of the format chosen, the end result of the pro-gram is to gather data from frequent purchas-ers and, of course, to deliver ROI without re-ducing margins.

Actually doing something with the data refers to effective tracking and analysis that finds actionable insights in this data-rich re-source. Users of this data include members of the sales, marketing and merchandising teams.

Another effective user group is the loyalty

with vast potential to engage shoppers. And cell phones, by virtue of being carried every-where by shoppers, are the most intimate channel of all. So it’s not surprising to see half of retailers making investments in the social and mobile channels.

Overcoming ObstaclesThe number one obstacle retailers say they need to overcome is defining and creating ef-fective loyalty programs, which was chosen by 53.1%. Coming in a close second is “actually doing something with data already in hand” (50%). These may sound like similar issues but they are not. (See Figure 6.)

Defining and creating an effective loyalty

customers comprise a large portion of every successful retailer’s customer base it seems logical that retailers would analyze purchas-es by this segment and use the insight to set sales targets and forecasts. We find this is true for 29% of respondents.

This means the remaining seven out of 10 retailers do not effectively use this type of information. The most likely reasons are that they do not trust their loyalty data or do not make the data easily available to the sales, marketing and merchandising departments to improve the accuracy of sales, inventory and budget forecasts.

Even fewer retailers use loyalty data for predictive analysis or use it to create tests in micro customer segments. Both of these functions are currently being carried out by 16.1% of respondents, a small portion.

As retailers gradually embed analytics throughout their enterprises such sophisti-cated test-and-learn programs like these will move higher on the priority list.

Future PlansSo far we have benchmarked the loyalty mar-keting capabilities in use today, but what are retailers planning to invest in tomor-row? Topping the list are two of the biggest trends spreading throughout the marketplace – multi-channel data integration and the in-creasing use of analytics to understand cus-tomer behavior, both of which were selected by 56.3%. (See Figure 5.)

As retail becomes an omnichannel indus-try it is imperative that two things happen: data integration occurs across all channels and analysis identifies the lifetime value of single-channel and multi-channel customers. A multi-sales-channel view of the customer is therefore the new reality in retail. The next step is to mine this rich database to find growth opportunities that no other competi-tor has access to.

Not much farther down the investment priority list in this chart is social and mobile channel engagement, which was selected by 50% of respondents. Social networks are key enablers of highly personal communication

Multi-channel data integration

Analytics to understand customer behavior

Pricing and communications personalization

Marketing program, communication frequency

Social and mobile channel engagement

Loyalty/rewards program rollout

Customer usage and attitudes data acquistion

Loyalty systems upgrade, enhanced loyalty rewards

53.1%

50%

50%

46.9%

37.5%

25%

56.3%

56.3%

Defining and creating effective loyalty programs

Actually doing something with data already in hand

Lack of system that allows easy access to customer data

Overcoming past practices that were ineffective

Getting customers to provide data

Lack of a single repository to house data

Lack of data science skills and staff in organization

46.9%

37.5%

34.4%

28.1%

25%

53.1%

50%

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Page 6: Manthan Systems – Loyalty Management

R I S N E W S . C O M M AY 2 0 1 3 6

From the shopper’s perspective, what are the drivers of customer loyalty?

What is the status of measurements/KPIs that track loyalty efforts now, by end of year and within 18 months?

F I G U R E 8

F I G U R E 9

F I G U R E 7

dia and direct mailings. Finally, we asked respondents to tell us

which retailers they thought were leaders in leveraging customer data to create relevancy with their customers. The top vote getters are Amazon, Nordstrom and tied for third place are Macy’s and Tesco. (See Figure 9.)

Amazon pioneered many of the frequent shopper technologies currently deployed throughout the e-commerce world today. Nor-

ers and a level of maturity in the evolution of loyalty programs. Whether it is true or not from a shopper’s perspective is open to de-bate, because shoppers love giveaways. But this is beside the point. Retailers do not make money by giving away awards and discounts. However, they clearly have the potential to create loyalty and engagement by serving up personalized offers and communications through e-mail, mobile messages, social me-

department itself. The data can be analyzed to discover why churn or drop outs occur. Then steps can be taken to re-engage once-loyal shoppers. Many retailers have discovered that re-engaging formerly loyal shoppers results in a sharp increase in frequency and market basket size.

KPI Priorities and PlansIn addition to designing an effective loyalty program from the front-end (customer-facing) and balancing back-end concerns (ROI, mar-gin preservation and driving sales), retailers need to create hierarchical database models that have carefully selected attributes so that it is easy to aggregate and distribute key per-formance indicators (KPIs). (See Figure 7.)

We asked retailers about the current KPIs they track and what is on their to-do list to add by year’s end and in 18 months. Today, we find the majority of retailers are track-ing the following: sales by customer segment (75.9%), customer conversion rate (67.9%), offer redemption rates (64%), customer re-tention rates (60%), recency, frequency, mon-etary (56.5%), and member versus non-mem-ber spending (55.6%).

Over the next 18 months the top two areas retailers will begin tracking are customer life-time value (40.9% will add by year’s end and 27.3% will add in 18 months) and customer acquisition cost (38.1% will add this year and 33.3% will add in 18 months.)

Loyalty Program PerspectivesTo wrap up the loyalty program report we asked two questions about respondent per-ceptions. The first is the kind of question not normally asked of retailers but one that is es-sential to know: What do shoppers want and think is important to them?

Retailers said they believe the top driver of customer loyalty from the shopper’s per-spective is relevant and personalized offers and communication, chosen by 83.9%, which comes in ahead of awards and discounts, which was chosen by 74.2%. (See Figure 8.)

This is an important finding because it shows a growing sophistication among retail-

Sales by customer segment

Customer conversion rate

Offer redemption rates

Customer retention rates

Requency, frequency, monetary (RFM)

Member vs. non-member spend

Customer lifetime value (CLV)

Customer acquisition cost

•Have Now •Will Add by Year’s End •Will Add in 18 Months

75.9%

67.9% 21.4%

28%

28%

34.8%

33.3%

40.9%

38.1%

64%

60%

56.5%

55.6%

31.8%

28.6%

17.2% 6.9%

10.7%

8%

12%

8.7%

11.1%

27.3%

33.3%

Relevant personalized offers and communications

Awards and discounts

Active participation in the community (via social media, etc.)

Special services based on membership

83.9%

74.2%

41.9%

32.3%

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Top reTailers ThaT leverage cusTomer daTa To creaTe relevancy wiTh Their cusTomers

Amazon

Nordstrom

Macy’s, Tesco (Tied)

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Page 7: Manthan Systems – Loyalty Management

R I S N E W S . C O M M AY 2 0 1 3 7

opportunities for growth that no other com-petitor has access to. The customer has the power to control the shopping experience to-day, but the retailer has the power to control the data. RIS

dstrom famously developed an unparalleled store-level frequent shopper program and has spent the last five-plus years converting it into an omnichannel success.

Tesco pioneered the application of data-base sciences to the retail model, especially in the area of customer segmentation, and has used this intelligence to fuel international ex-pansion. And Macy’s has used elements from all of the above to transform a collection of local department store chains into a thriving national brand.

Each of these four highly successful retail-ers continues to grow through good times and bad largely because of the ability to under-stand their customer’s wants and needs at a detailed database level.

MethodologyThis study was conducted during the month of April and only senior executives from na-tional or large regional retailers were invited to participate. The results do not include any store-level, field-level or regional employees. Only headquarters-level staff responses were included.

ConclusionAs the popularity of loyalty programs increases most retailers today view them as valuable tools for power users in sales, marketing and merchandising. And yet many retailers still un-derutilize loyalty programs and databases due to a scattering of responsibilities across mul-tiple departments and multiple IT systems. As a result, loyalty program members are often no more loyal to retailers than other customers.

However, this is changing as savvy retailers such as Amazon, Nordstrom, Tesco and Ma-cy’s lead the way to a new and profitable level of customer engagement and loyalty.

A major theme that emerges in the study indicates that the ability to aggregate purchase data across all channels, update it frequently, and then break it into key segments is a path-way to success.

Another interesting finding is that nine out of 10 retailers do not use packaged loyalty solutions. There is a significant opportunity awaiting vendors to demonstrate clear value in their loyalty solutions. However, retailers won’t wait and will create their own solutions in a vacuum.

As retail becomes an omnichannel indus-

try and the pace of innovation accelerates it is imperative that retailers have the tools to analyze a 360-degree view of their best cus-tomers. But this is not enough. The ultimate step is to mine a rich loyalty database to find

What was your organization’s sales performance in the most recent 12-month period?

What is the status of your marketing technology budget for 2013 compared to 2012?

F I G U R E 1 1

F I G U R E 1 2

What is your organization’s annual revenue?

F I G U R E 1 0

$100 million to $500 million

$500 million to $1 billion

$1 billion to $5 billion

$5 billion or higher

28.1%

28.1%15.6%

12.5%

15.6%

Less than $100 million

Decreased

Increased more than 5%

Increased up to 5%54.8%

25.8%

19.4%

Remained flat

Decreased Increased by more than 10%

Increased by 5% to 10%

Increased by up to 5%

12.9%

16.1%3.2%

38.7%29%

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