As the US and the world economies encounter a downturn and firms look to scale back, Marketing is often one of the first places to face budget cuts.  Forrester reports that many companies expect to cut their marketing budgets by 3%.  But how do you maintain or grow your customer base and revenues when consumers are spending less and your message isn’t getting into the marketplace as loudly?

We think the use of online coupons deserves a harder look.  Emailing your customers and prospects with newsletters, product updates, and coupons is certainly nothing new, but it’s now well-positioned for even greater success:

• Companies are getting good at it. After dabbling in techniques like SEM and direct email, firms have gotten better at driving profitable growth from these methods, and many are increasing their focus on online advertising as a cheaper way to spend their marketing dollars. 
• Consumers want more of it. During these uncertain times, consumers plan to increase their use of coupons to save some money.  Sending these options straight to their inbox or mobile phone accomplishes that goal and positions you as a preferred provider.
• Consumers who use it are attractive prospects. Compared with consumers who only use offline coupons, Forrester reports that users of online coupon tend to have higher incomes, shop online, like to try new products, and influence peers.  Younger consumers also use coupons, and they can be a good avenue to get the word out about your product.
• More data is available to help you win at it. More firms sell marketing lists (or can help you run campaigns to get new lists), segmentation data helps you understand consumers’ preferences and desires, and syndicated data helps you understand purchase behavior.  Combining this data gives you incredible insight into consumers to tailor unique marketing messages.

You don’t just want to throw promotion dollars at existing customers to give them discounts on things they were already going to buy; rather, you likely want to use those dollars to deliver positive returns and achieve business goals – such as acquiring new customers, increasing market share, or increasing wallet share.  Doing this requires targeting offers to customers based on their stage of the customer life cycle:

1. Acquire. Coupons can be a good tool to help consumers overcome the risk associated with trying a new product; if a new product is cheaper than the one they normally use, the savings might be worth trying.  You can use them to attract entirely new customers to your firm, or to get your existing customers to try a new product line.  Targeting early adopters can also help generate buzz, as they will influence friends and family to buy the product as well.
2. Grow/Stimulate. Once you’ve acquired a customer, you want them to maintain or increase their purchases.  Two ways of stimulating usage are encouraging them to try a different variety (e.g., color, size, flavor) or showing them new uses for the same product (e.g., using Q-tips for craft projects in addition to hygiene).  In this stage, the focus should be on the marketing message, the coupon being used to help seal the deal and drive the customer to the store.
3. Manage. In this stage, your customers are steady-state users, and couponing may not be required to retain them. However, these consumers present a good opportunity to test new offers on an already loyal customer base and measure the response before using them on the general public.  You might test them using different demographics, layout, or wording, perhaps even running controlled experiments to determine which of two offers is more effective.  We’ve done some research on the use of Behavioral Economics to improve offer design, which might be helpful in performing this testing.
4. Reclaim. If customers reduce their consumption or begin to try competitors’ products, you can use targeted offers to reintroduce your product and retain them as customers.  However, depending on their needs and your product pipeline, you may otherwise opt to move back to the beginning of the life cycle and acquire them as customers of another of your products.

This strategy requires a high level of customer insight to understand preferences and stages in the life cycle.  You can gain this insight by applying segmentation schemes to your lists of customers and prospects, and by analyzing your customers’ history of purchases and coupon redemption.  Applying a rigorous testing approach will help you identify the most effective offers for each customer and stage.

Applying this framework to understanding your customers and targeting coupons will deliver several benefits, including:

1. Strong ROI potential.  Campaigns that are more effective and lower-cost, targeted at attractive customers, have a stronger potential to deliver a positive ROI.
2. Better data to analyze results. Results of online campaigns are easier to track and measure than traditional campaigns, particularly if your coupons lead customers to purchase from your own website.  Analyzing results from campaigns that involve multiple partners may require a different approach, as Vishal outlined in his earlier post on trade promotions.
3. Better customer relationships. You can use the insight you’ve gained about your customers’ behaviors, preferences, and purchase history to continually develop targeted offers.  This level of personalization will help you deliver the right offers to the right customers at the right time, and ensure that your promotion dollars are spent most effectively.

Some recent academic literature has shown that companies using the standard Net Present Value (NPV) approach to calculate Customer Lifetime Value (CLV) and allocating their marketing spending might be losing substantial profits.

The standard CLV approach calculates the net present value (NPV) of all the anticipated cash flows coming in (revenues) and going out (expenses) over the projected life time for a given customer. Customers with a positive NPV are aggressively marketed and the ones which do not have a positive NPV are dropped. This is a pretty logical choice at the point of calculation- but only then. The existing conventional structure of calculating CLV is static and has the potential to leave money on the table for the company; because it does not account for the fact the company has the flexibility of abandoning a customer at any future point in time. Flexibility means options and options have a value.  The paper lays down a methodology (based on dynamic programming) to explicitly estimate the value of such options in the CLV calculation.

The authors of the paper cite the example of a specialty catalog company. They took data of 12 years and around 100,000 customers, and the difference in CLV using the traditional versus real options was as much as 20% in some cases. In fact, certain customers who had negative CLV’s turned positive when the value of real options was considered.

Retailers, communication companies and consumer finance companies who frequently use CLV as a decision making metric, are strongly recommended to read this paper.

A set of whitepapers for the executive who wants to leverage the data to make smart marketing investments:

1. Identifying attractive markets and understanding your customers
2. Increasing online sales
3. Focusing on profitable distribution partners
4. Improve customer experience through call center data
5. Retaining your customers

Not many of us think about Amazon’s free shipping offer as a rewards program. That is exactly the point Jack is making as he classifies Amazon’s free shipping offer as a continuous reinforcement schedule. He uses a schedule of reinforcement framework proposed by psychologist B.F Skinner and applies it to rewards programs.

A continuous reinforcement schedule is dangerous. At best, the promotion shows a little lift in the short term and a huge decay in the long term (doing nothing in terms of real loyalty). At worst, you unintentionally create new business rules for your company. When those rules inevitably change, you alienate people who migrated to your company because of them. You even risk teaching users new behaviors that are bad for business

Apart from continuous reinforcement, the other reward categories are:

• Fixed ratio (SUBWAY’s “buy 12 feet, get one foot free”) and variable ratio rewards (lottery)
• Fixed interval (Restaurant happy hours) and variable interval rewards (radio contests that grant prizes “sometime this hour”)

It is an interesting framework to generate hypotheses for rewards programs, which need to be then quickly tested in the market and analyzed to determine the most financially positive program structure.

We earlier wrote about some recent academic literature on customer loyalty and highlighted the importance of a good market testing and campaign management capability to determine the optimal rewards program structure.

In any customer facing business, the channels used to reach out to your customer as well as the channels your customer use to consume your products and services have a strong correlation with overall profitability. 

From the B2C perspective, advertisements, stores, online, mailers, charity, etc. are different ways of reminding customers about your offerings. From a C2B perspective, again, stores, online, home delivery orders, etc. are ways in which consumers consume your products. 

However, the key here is to understand which customer prefers which B2C and which C2B channel. Right-Targeting Customers is as important as Targeting Right Customers! Someone who spends 14 hours a day in front of his computer and has no time to go to a store 5 days a week may prefer a home delivery channel. On the other hand, a student in a college is only interested in the bargain channel, irrespective of the inconveniences, maybe. This report also mentions how retailers need to manage their investments across channel against the scale and timing of their expected return. I would go beyond Ron’s Right Channeling [read post] to include all aspects of targeting under the concept of Right-Targeting. Having said that, I agree that today’s world is about multi-channel customers, and the need of the hour is to optimize channel returns, rather than just channel re-alignment/phase-out. 

Targeting Right Customers- Its equally important is to understand how channel profitability gets affected if you are not targeting the right customer. For instance, Wal-Mart, even with its Everyday Low Prices (EDLP), must be making money on some products/ some SKUs and these would drive the overall positive profitability. However, what if your customers are not buying your profitable SKUs? What if the draw that brings them there is not luring them to buy more? What if there is no up sell/cross-sell/bundling that happens there? And suddenly the business realizes that channel profitability is coming under immense pressure! (One of our earlier posts tries to answer the question of market basket analysis and product bundling). 

Re-Targeting - And last but not the least– taking the difficult decision of phasing a channel out. If it’s not generating any returns (directly or indirectly), the business needs to reconsider the cost of the channel. But what about retaining those customers who are loyal to the channel and have helped you get some mileage out of it? They need to be Re-targeted with a new offering/communication. Traditional retargeting refers to targeting customers who did not convert the last time, though!

This report (PDF) here talks about issues to be kept in mind when moving customers from one channel to another. I am sure Kevin would want to talk about Multi-channel customers being better than single channel customers, and without refuting his argument I would classify my argument as being restricted to customers that are being phased out of a channel. This example demonstrates one case where the retailer has effectively leveraged multiple channels over a period of time by effective use of catalogs and internet channel. 

In Summary

• Right Targeting – Know your customer. Cater to their needs through their preferred channel. It increases the share of wallet, as well as longevity of the customer
• Targeting Right – Pick your customers for each channel-product combination well. Know what and how you are selling and who will buy it.
• Re-Targeting – If it’s imperative that you move away from a particular channel, think about retaining your loyal channel customers. A little caring goes a long way in creating customer loyalty.

The qualifying argument behind all this is that if you are thinking about channel optimization, it needs to be a more concerted discussion based on your strategy/business objective, your data, your needs and your concerns. What we know for sure is that strong data analytics is known to help not only Targeting Right (which is the most common application), but Right Targeting, as well as Re-Targeting.

A discussion I had with a group of analysts suggested, based on rigorous data analytics, that rewards points and redemptions as value added services do help credit card companies retain a few more customers [This image here does prove the retention hypothesis], but its a huge cost on the account level P&L⁽¹⁾. Probably, one of the worst rewards offer is Air travel related redemptions. So, if you are a credit card company and you want to advertise your rewards catalogue, be cautious about advertising Airlines Redemption, is what the group suggeted.

The premise of rewards program offered by credit card companies, traditionally, has been low redemption rates and a lot of people not even redeeming their points ever. Add to it the hassles faced by customers in redeeming, you have defeated the purpose of the program. Why offer a value added service you don’t want people to use (and create negative customer experience)? And, just in case someone ends up using it, why compound the problem with an unfavorable cost structure for such a service?
Assuming that rewards programs are aimed at retaining customers, are the redeemers those customers whom I want to retain through this offering? In other words, am I retaining the right customer?

Lets focus on the second question - Who is the right target for these rewards? Someone who stretches the margin the most (through frequent high cost redemptions, hitting P&L through rewards costs as well as high customer servicing costs), or someone who is generating good revenues through revolving credit, relatively infrequent bulkier redemptions and is sticking on to the credit card because of a certain variety of reward?
Offering rewards as a retention ploy would imply ceilings and floorings to redemptions (by type) for managing customer profitability. For instance, credit card companies impose hypothetical floorings by allowing air ticket redemptions only if someone is utilizing at least 20,000 points or more.

• Another strategy for rewards programs could be aimed at identifying customers with a lower propensity to redeem while maintaining a higher retention probability given rewards utilization.
• However, the best strategy in such cases would be to build multi-stage rewards and retention model that predict point balance utilization, preferred category of redemption, retention driven by rewards usage and most importantly, P&L sensitivity models for rewards usage. This requires deep analytics expertise and a thorough understanding of credit cards’ rewards program.
• Additionally, this report coming through Celent highlights how rewards disposition is likely to change going forward and move towards blended rewards and cash-backs and the economics are likely to become more favorable by leveraging low cost internet, mobile advertisement channels.

⁽¹⁾For P&L, however – lets look at this example⁽²⁾

Include the various maintenance cost items, program costs, and servicing costs on top of the air ticket cost and you probably end up with a non-existent or a very “thin” margin!
⁽²⁾ Under the assumption of zero revolving credit and other sources of revenue that credit cards’ companies generate. While revolving credit is the biggest source of money for credit card companies, the attempt here is to show that at the base level, the credit product is becoming unprofitable because of a faulty rewards program
⁽³⁾ Optimistic, my friends tell me!

Jay recently posted a comment asking us to elaborate on our churn heat map posting. The best way to explain is to show an actual churn heat map which we created for a client.

• Height of each row represents % of all activations
• Each row split into three parts –returns, voluntary churn, and involuntary churn, from left to right, with the % of total churn in that row determining width
• Particularly high or low levels of each type of churn are indicated by color, providing a “heat map” for where the largest churn issues reside

Depending upon your organization, you can choose what segments/sub-segments and products to use to create the heat map

For an executive this churn visual gives a starting point for generating hypotheses and serves as a useful reporting tool to see the efficacy of churn reduction activities