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RIS News Custom Research

The Power of Emotional Connections Effective loyalty management needs to shift from being an underutilized resource to becoming a force for driving engagement and growth

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By J o e S ko ru pa

The Power of Emotional Connections Effective loyalty management needs to shift from being an underutilized resource to becoming a force for driving engagement and growth Loyalty is a complex, emotional connection that occurs between a shopper and a brand. It is built over time through a combination of drivers. These drivers include marketing, merchandising, pricing, product mix, product satisfaction, shopping 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 shoppers required to support a retail business. Instead, an aggregation 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 example, 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 retailer perceptions of loyalty programs. At a basic level, a loyalty program creates unique customer profiles that enable tracking of purchases. In many cases, purchases are converted into points and awards (although not all membership programs offer rewards based on points). In all cases, however, the information collected in loyalty databases is intended to be a resource for marketing and promotional campaigns. But the operative word here is “Intended.” The truth is that retailers frequently underutilize their loy-

Getting Personal with Analytics It 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

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alty program capabilities and databases. One reason is the absence of an effective loyalty management and communication tool. Other reasons include dispersed databases that make it difficult to synch up customer profiles and purchase histories, often due to a scattering of responsibilities across multiple departments using multiple IT systems. Without effective tools and strategies to foster engagement, loyalty program members are no more loyal to retailers than other customers. 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 Full A little over half of retailers (56.3%) either update loyalty data frequently and break it into segments and profiles or they collect aggregated customer data across all channels (53.1%). These are the prerequisites for making effective 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. Members in this group either do not believe their niche is well suited to loyalty marketing or instead believe their efforts are better focused on other strategies, such as everyday low prices, for example. Interestingly, we see evidence of an emerging 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 augmented 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-

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

56.3%

Data is frequently updated and broken into segments/profiles

53.1%

Collect aggregated customer data across all channels Individual customer purchase data not collected

25%

Customer purchase history is augmented with opt-in personal information

25%

Customer purchase history is augmented with social graph information

15.6%

F I G U R E 2

What are your current analytics capabilities?

Good, allowing management of customer data and customer segments

25% 31.3%

15.6% Decent, generating basic reports

version rates for marketing campaigns. But before moving up to this advanced level, 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 question about what retailers can actually do with data they collect. When we asked respondents to self-assess their customer analytics capabilities 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

Advanced, enabling delivery of personalized communications and offers

28.1% None, currently researching options

sophisticated group is split into two distinctive categories – 31.3% who say their capabilities are “good” because they allow some management of customer data and 25% who say their capabilities are “advanced” enough to enable delivery of personalized communications and offers. The remainder of the respondent pool either has limited customer analytical capabilities 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-

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

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

Loyalty Program Tools Even retailers that do not have purpose-built loyalty software possess some type of technology 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 services. 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 assessment 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 retailers base their negative perception on loyalty 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 industries. 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 improvements in key performance indicators. Nine out of 10 retailers would likely open their doors to vendors like these.

46.9%

Custom software built in-house 28.1%

Packaged CRM solution

25%

Third-party outsourced services

18.8%

None Packaged loyalty solution Data sharing with suppliers for customer analysis

9.4% 3.1%

F I G U R E 4

What are you doing with your customer and loyalty data? 48.4%

Delivering targeted offers and communications to specific segments

41.9%

Tracking for historical analysis and points/rewards program management 32.3%

Analyzing purchases to drive cross-selling opportunities

29%

Setting sales targets and forecasts Nothing, do not strategically use customer or loyalty data

19.4%

Creating tests in micro segments

16.1%

Performing predictive analysis to improve forecasting accuracy

16.1%

What Do You Do with the Data? Regardless of the type of technology retailers have we wanted to find out what loyalty marketing techniques they most frequently use to drive sales. Not surprisingly, the top technique is delivering targeted offers and communications 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 necessary first steps on the maturity ladder. (See Figure 4.) A more advanced technique is analyzing purchases to drive cross-selling opportunities,

which is currently being used by 32.3% of respondents. 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 purchasers of cell phones. Or it could be a coupon for lawn furniture sent to recent purchasers 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

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customers comprise a large portion of every successful retailer’s customer base it seems logical that retailers would analyze purchases 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 sophisticated test-and-learn programs like these will move higher on the priority list.

Where are you planning to invest within loyalty marketing? 56.3%

Multi-channel data integration Analytics to understand customer behavior

56.3% 53.1%

Pricing and communications personalization Marketing program, communication frequency

50%

Social and mobile channel engagement

50% 46.9%

Loyalty/rewards program rollout 37.5%

Customer usage and attitudes data acquistion Loyalty systems upgrade, enhanced loyalty rewards

25%

F I G U R E 6

What obstacles need to be overcome in your organization to effectively use loyalty data and a loyalty solution? 53.1%

Defining and creating effective loyalty programs Actually doing something with data already in hand

50% 46.9%

Lack of system that allows easy access to customer data 37.5%

Overcoming past practices that were ineffective

Future Plans So far we have benchmarked the loyalty marketing capabilities in use today, but what are retailers planning to invest in tomorrow? Topping the list are two of the biggest trends spreading throughout the marketplace – multi-channel data integration and the increasing use of analytics to understand customer behavior, both of which were selected by 56.3%. (See Figure 5.) As retail becomes an omnichannel industry 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 competitor 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

34.4%

Getting customers to provide data Lack of a single repository to house data Lack of data science skills and staff in organization

with vast potential to engage shoppers. And cell phones, by virtue of being carried everywhere 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 Obstacles The number one obstacle retailers say they need to overcome is defining and creating effective 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

28.1% 25%

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 program is to gather data from frequent purchasers and, of course, to deliver ROI without reducing margins. Actually doing something with the data refers to effective tracking and analysis that finds actionable insights in this data-rich resource. Users of this data include members of the sales, marketing and merchandising teams. Another effective user group is the loyalty

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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.

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

Customer conversion rate

67.9%

Offer redemption rates

64%

17.2%

6.9%

21.4% 10.7% 28%

8%

Customer retention rates

60%

28%

Requency, frequency, monetary (RFM)

56.5%

34.8%

8.7%

Member vs. non-member spend

55.6%

33.3%

11.1%

KPI Priorities and Plans In addition to designing an effective loyalty program from the front-end (customer-facing) and balancing back-end concerns (ROI, margin 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 performance 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 tracking the following: sales by customer segment (75.9%), customer conversion rate (67.9%), offer redemption rates (64%), customer retention rates (60%), recency, frequency, monetary (56.5%), and member versus non-member spending (55.6%). Over the next 18 months the top two areas retailers will begin tracking are customer lifetime 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.)

75.9%

Sales by customer segment

Customer lifetime value (CLV) Customer acquisition cost

31.8% 28.6%

40.9%

12%

27.3%

38.1%

33.3%

•Have Now •Will Add by Year’s End •Will Add in 18 Months F I G U R E 8

From the shopper’s perspective, what are the drivers of customer loyalty? 83.9%

Relevant personalized offers and communications

74.2%

Awards and discounts Active participation in the community (via social media, etc.) Special services based on membership

41.9% 32.3%

FIGURE 9

Top retailers that leverage customer data to create relevancy with their customers

Amazon Nordstrom

Loyalty Program Perspectives To wrap up the loyalty program report we asked two questions about respondent perceptions. The first is the kind of question not normally asked of retailers but one that is essential 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 perspective 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-

Macy’s, Tesco (Tied)

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 debate, 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-

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-

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Custom Research 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 database sciences to the retail model, especially in the area of customer segmentation, and has used this intelligence to fuel international expansion. 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 retailers continues to grow through good times and bad largely because of the ability to understand their customer’s wants and needs at a detailed database level.

Methodology

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What is your organization’s annual revenue?

12.5% $100 million to $500 million

As 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 underutilize loyalty programs and databases due to a scattering of responsibilities across multiple 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 Macy’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 pathway 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-

15.6%

28.1%

$1 billion to $5 billion

$5 billion or higher

F I G U R E 1 1

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

This study was conducted during the month of April and only senior executives from national 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.

Conclusion

28.1% 15.6%

Less than $100 million

$500 million to $1 billion

25.8% Decreased

Increased more than 5%

54.8% Increased up to 5%

19.4%

F I G U R E 1 2

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

38.7% Remained flat

29%

12.9% 3.2% Decreased

Increased by up to 5%

Increased by 5% to 10%

16.1%

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

Increased by more than 10%

opportunities for growth that no other competitor has access to. The customer has the power to control the shopping experience today, but the retailer has the power to control the data. RIS RIS NEWS.COM

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Manthan Systems – Loyalty Management  

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

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