Refer a friend programs: are they worth it?

September 6, 2010 By 2 Comments

Refer a friend programs: are they worth it?  Yes, as it happens they are and some very recent research gives us the numbers to back it up.

Referral Programs and Customer Value was recently published by Schmitt, Skiera and Van den Boulte.  In this excellent paper, rigorous analysis was applied to a topic of discussion by marketers the world over: do ‘refer a friend’ programs make money?

Their findings: customers acquired through paid customer referral programs have a higher retention rate and higher initial contribution margin than other customers.  In other words, yes they do work.

In this post from last week “Using social effects to improve customer retention”, we looked at how client referrals can work in reverse.  Losing a client increases attrition for the people already in their social network.  Now we have proof that the positive reverse is also true.

What this means is that the effort invested into so called stimulated word of mouth (WOM) programs generate real and valuable client referrals.

The entire paper (in truth, perhaps not the statistical methods section) is interesting because of the completeness with which the authors address the question of successful referral programs.  For instance they discuss why customers acquired through client referrals are a better match (and higher margin) for the organisation than the average acquired customer:

  1. Reciprocity – the person performing the customer referral feels that they owe (because a payment is involved) the company a good customer.
  2. Triadic balance – where the propensity of two people to feel the same about an object (in this case company) make the friend in “refer a friend” more likely to like the company.
  3. Homophily – people have friends that are similar to themselves.  If I like, or am a good customer, for this company so will be my friend.

Getting back to the source data, the authors were able to access substantial (approximately 10,000) customer records and watch their progress over a 33 month period from acquistion.  This allowed them to review not just the initial margin but also look for differences in retention rate and long term margin rates.

For practical marketers the key outcomes from this paper include:

  1. Higher gross margin levels: customer referrals showed an initial 25% higher contribution margin than non customer referrals.  However, the difference reduced over time to be similar at the 29 month mark.Customer-Referral-Programs-Margin
  2. Better retention rates: customers acquired through referral programs have a higher retention rate and that difference does not reduce.Customer-Referral-Programs-Retention-Rate
  3. Client referrals generate higher value customers: taking (1) and (2) together, customers obtained through successful referral programs are of higher overall value than other customers.  For the authors that difference was 25%, i.e. customer referrals were 25% more valuable than non-customer referrals.
  4. Customer referral programs are a good investment: the net increase in value more than pays for the cost of the reward.  This is of course subject to reasonable reward costs.  In the case of this study the reward cost was 25 Euros, which was more than covered by the 25% increase in value.
  5. Abuse costs less than the increase in value: The costs of progam abuse and other negative side effects of customer referral programs were smaller than the increase in value.

In many practical ways the authors have made our lives easier as marketers by proving the value of customer referral programs.  Some of the debate can now cease and we can focus instead in creating successful referral programs for our companies.

By Adam Ramshaw

Filed Under: Customer Analytics, Customer Loyalty Management Tagged With: , ,

New Insights: Net Promoter Score Vs Customer Satisfaction

August 15, 2010 By 2 Comments

Recently we performed some Net Promoter Score comment coding work for a successful Australian health fund called nib health insurance.  nib has recently de-mutualised and as a result is very focused on providing its customers with the best levels of service possible.

Towards the end of 2009 nib investigated the use of NPS and in January 2010 they started to use transactional Net Promoter Score, i.e. they have started to collect NPS scores and comments for a variety of customer touch points.

Since then they have collected a large volume of free format comment data.  Our task was to help them identify a set of comment themes for their data and then code the comments by the different themes.  To be sure, it was a substantial task.

In the process, though, we uncovered a very interesting insight that they have been kind enough to allow us to share.

The nib survey process uses best practice transactional Net Promoter Score approaches; they contact the customer shortly after each touch point interaction and perform a short email survey.  What is unique about the survey that nib perform is that they ask for a “customer satisfaction” score and comments along with the “would you recommend” score and comments.

This leads to rather good opportunity to compare what customers include in their analysis process when they score customer satisfaction and Net Promoter Score.

We used the same set of themes to code the data for both Customer Satisfaction and Would Recommend question.  The chart below looks at how often each of the themes was coded for each question.

In the coding process we only identified the theme of the comment, not whether it was positive or negative.  So the volumes that you see in the chart are representative of the customer’s perceptions of the relevance of that theme to either the customer satisfaction (CSat) or “would recommend” (NPS) question.  Each comment could be coded for more than one theme.

The first area to note is the substantially different theme coding rates for “would recommend” and CSat.  Very few themes are coded consistently between the two questions.  You will also notice that the NPS themes are coded more evenly.  The maximum coding rate for NPS is about 16% but for CSat it peaks at 31%.

Also, almost all of the themes are coded above the 1% rate for NPS while only 60% of the CSat theme are coded at the same rate. This implies that customers consider a wider array of elements of the overall offering when responding to the “would recommend” question than when they respond to the CSat question.

From this we can say that the NPS question appears to be a more rounded review of the business.

If we dive down into a couple of specific themes this distinction becomes even more evident.  For instance you can see that Speed of Service and Staff Attitude is top of mind for customers when considering CSat but not considered as often when answering the NPS question.

On the other hand, pricing attributes are rarely considered when the customer provides feedback on CSat but for NPS they are coded relatively often.

As I say this was an imperfect, but relatively unique, opportunity to compare the areas that customers consider when providing a “customer satisfaction” or “would recommend” score.  However, because it was not designed from the outset to test the different themes customers considered when scoring the two questions we must be careful not to overestimate the significance of these results.

For instance the order of the questions was always the same.  This may lead to bias in the response.  If you were to design this as an experiment from the ground up you would ensure that each question was shown first 50% of the time.

However, even allowing for its imperfect experimental design, it is a very interesting result.  The work undertaken by the originators of NPS (Fred Reichheld et al) included a comparison of correlation to revenue growth of several different potential leading indicator questions, including customer satisfaction and “would recommend”.  The outcome of that research showed that CSat was a less good predictor of revenue growth than NPS.

Perhaps in these results we can see part of the reason that CSat is less good as an indicator of future business growth.  Our hypothesis here is that because customers refer to fewer themes in their responses to the CSat question than the NPS question, CSat focuses more explicitly on the immediate service experience.

Note though that while the immediate service experience may be more important for the CSat score, i.e. it may be skewed towards areas that are important for that experience, it may not cover all of those elements required to drive higher customer loyalty.

Potentially, customers consider a much wider range of areas in the total offering when answering the NPS question.  Thus, the NPS question is a broader and more holistic response and better aligned to overall customer loyalty.

Once again we would like to acknowledge the support of nib in allowing us to publish these findings.

For more information on Net Promoter Score and how/why it works download our free Introduction to Net Promoter Score (NPS).

If you are thinking about implementing Net Promoter Score (NPS) in your organisation give us a call. We can help you to measure word of mouth through an effective Net Promoter Score program for your business.

Net Promoter, Net Promoter Score and NPS are registered trademarks of Bain & Company, Inc., Satmetrix Systems, Inc., and Fred Reichheld.

As I say this was an imperfect but relatively unique opportunity to compare the areas that customers consider when providing a “customer satisfaction” or “would recommend” score.  However, because it was not designed from the outset to test the different themes customers considered when scoring the two questions we must be careful not to overestimate the significance of these results.

For instance the order of the questions was always the same.  This may lead to bias in the response.  If you were to design this as an experiment from the ground up you would ensure that each question was shown first 50% of the time.

Even allowing for its imperfect experimental design, it is a very interesting result none the less.  The work undertaken by the originators of NPS (Fred Reichheld et al) included a comparison of correlation to revenue growth of several different leading indicator question possibilities including customer satisfaction and “would recommend”.  The outcome of that research showed that CSat was a less good predictor of revenue growth than NPS.

Perhaps in these results we can see part of the reason that CSat is less good as an indicator of future business growth.  Our hypothesis here is that because customers refer to fewer themes in their responses to the CSat question than the NPS question, CSat focuses more explicitly on the immediate service experience.

The immediate service experience may be more important for the CSat score, i.e. it may be skewed towards areas that are important for that experience.  However, it may not cover all of those elements required to drive higher customer loyalty.

On the other hand customers consider a much wider range of areas in the total offering when answering the NPS question.  Thus, the NPS question is a broader and more holistic response and better aligned to overall customer loyalty.

Once again we would like to acknowledge the support of nib in allowing us to publish these findings.

For more information on Net Promoter Score and how/why it works download our free Introduction to Net Promoter Score (NPS).

If you are thinking about implementing Net Promoter Score (NPS) in your organisation give us a call. We can help you to measure word of mouth through an effective Net Promoter Score program for your business.

Net Promoter, Net Promoter Score and NPS are registered trademarks of Bain & Company, Inc., Satmetrix Systems, Inc., and Fred Reichheld.

By Adam Ramshaw

Filed Under: Customer Feedback Process, Net Promoter Score Tagged With: , ,

Are you using campaign lead or customer lead marketing?

July 4, 2010 By 1 Comment

This week I’m going to build on a recent post (“Why customer segmentation is not customer strategy”) by looking at a new approach to creating a customer strategy.

We will start by examining how most marketing departments use customer segmentation.  Over the past 10-15 years an evolution, a good evolution mind you, has overtaken marketing organisations.  In that time there has been an increased focus on maximizing the return on marketing investment.

The Campaign Lead Approach

Through improved customer data and analytical software, organisations have constantly increased their campaign return on investment.  One of the tools that they have used to do this is customer segmentation.  A high level view of the overall marketing process and how customer segmentation fits is shown below.

Starting with the company’s business goals, organisations create marketing plans to meet those goals.  The marketing plans then take into account product opportunities, high level customer needs analysis and a range of other company specific attributes to create campaign ideas that are turned into campaigns.

The next stage of the process is critical in driving up campaign ROI: the campaigns are matched with customer segmentation data to find the customers that are most likely to respond to the campaign.  This matching process often uses past campaign/ customer segment performance as a guide in the matching process.

Lastly, the campaign is run.  The customer segmentation is used to extract a list of customers to whom the campaign will be sent.  The list is then passed through a range of customer exclusion rules.  These rules can be as simple as a “do not contact flag” or “never contact a customer more than once every 60 days”.  The final list is then merged with the campaign creative details (call script, direct mail piece, e-direct mail, etc) and sent to the customer.

This process can be used to deliver a campaign with a very high return on investment but it does have it’s problems.

  • The approach puts the campaign at the center of the process not the customer.  The approach is “We have a campaign now who can we send it to?”
  • Customers are not engaged in a conversation they are targeted with product sells and as one banking CEO said to me the other day: “Product pushing destroys customer relationships”
  • It seems that the same 20% of customers end up in almost all of the campaigns.  This is the 80/20 rule at work.  All of the A/B demographic customers seem to be dragged into all of the campaigns.
  • The organization focuses on creating high ROI campaigns but may miss opportunities with large portions of the customer base
  • Campaign results are tactical feedback in that the organisation can optimise the campaign but it may not be optimizing the value of the customer or business.

The customer strategy lead approach

A different, and I would say better, approach is to rather start with a customer strategy and work down from there.  That way you are optimising the value of the customer and business while also maximizing the campaign ROI.    Below is a customer strategy approach, the blue boxes are the changes from the original approach.

In contrast to the campaign led approach, the customer strategy lead approach is “We craft a customer journey unique to each customer and then deliver it to them over their lifetime with us, making sure to react to changes in their needs and activity.”

This is a completely different approach that builds trust and value in the customer relationship rather than destroying it.

  • Using this approach (a customer strategy and customer life-cycle approach), the customer is taken on a planned journey starting at the time they become a customer and take up their first product.
  • The campaigns/messages they receive are pre-planned and event based triggers.
  • At a campaign level, the result is a larger number of smaller, targeted campaigns offering higher ROI.
  • It is at the business level that the real value is found.  Using this approach you maximise the overall customer lifetime value.

It is true that in order to implement this approach you need a way to develop and assign a customer strategy to each customer.  In our experience a customer value map is the easiest and most direct route to creating a tool that can be used to assign a customer strategy to each and every customer.

If you would like to assess the areas where the best return-on-investment can be found, by targeting customers with the right current vs. potential value contact us about cpMAP: the customer value based customer strategy approach.

By Adam Ramshaw

Filed Under: Customer Analytics, Marketing Automation Tagged With: , ,

The 10 major marketing themes in 2000: still relevant?

June 27, 2010 By Leave a Comment

Every now and then I like to go back and read past work from the giants of our craft, and Philip Kotler certainly qualifies as a good set of shoulders for us to stand on so we can see further. In 2000 Mr. Kotler published “Marketing Management, Millennium Edition” (2000, Prentice Hall) and given the occasion, he looked forward and predicted the issues that Marketing would be dealing with in the new century.

Almost a decade into the 2000′s, I can say I think he was correct. He may despair that we are still to resolve the issues, but he was correct in identifying the major tasks in what we have (un-poetically perhaps) called ‘do marketing’.

So with comments based on our client work, here are the Kotler 10 from 2000. How well do you think we have got these under control in the last 10 years?

  1. Relationship Marketing – the view that a single transaction is too narrow a definition of our relationship with a customer, and that we need to understand the value of our customers across multiple transactions and know which of them are most important to us overall. Our customers are getting better at this, understanding that there is not an infinite supply of new customers and retention deserves attention. This insight leads to the next of Kotler’s issues;
  2. Lifetime Value - measure the value of a customer over multiple transactions, in fact over the lifetime of their relationship with you. Many organisations still struggle with this. The need for quarterly results focuses the mind of many customers on what I call the ‘disembodied sale’, thinking that sales exist independently of customers that you want relationships with and whose value you can measure over time.
  3. Customer Share - as opposed to market share. Is there a market without customers?
  4. Target Marketing - sell to all of your chosen customers since selling to all customers is not realistic.
  5. Individualization - treat different customers differently. Don Peppers said this first I think, in 1993.
  6. Customer Databases – data about customers rather / in addition to data about sales. The enabler of modern marketing, most customers are working on this, some have it under control but they are in the minority.
  7. Integrated marketing communications - there are so many channels for customers to choose from, it is important to balance and integrate your usage to match theirs. We agree.
  8. Channels as partners - everyone who represents your product to customers is a partner, not a passive channel.
  9. Every employee a marketer - your brand is the sum total of all customer interactions. Net Promoter Score (NPS) is a new and useful tool to measure how well you are doing with customers and employees at achieving this virtuous circle of customer and employee advocacy.
  10. Model-based decision making - more commonly called data driven marketing. Our solid believe is that ‘you should not guess when you can know’.

What do you think, have we made progress?

Filed Under: Customer Analytics, General, Marketing Automation Tagged With:

Why customer segmentation is not customer strategy

May 30, 2010 By 1 Comment

This recent blog article really struck a chord with me:  Why Doesn’t My Market Segmentation Work?

The author makes some good points and I agree completely with them but I wanted to go one step further.  I believe that customer segmentation often “does work” in that the answers you receive are completely, technically, correct.  But in practice it doesn’t work because while it is correct there is often no way for the business to use the information generated.

Recently we started working with a major financial services firm who had just completed a six month multi-hundred thousand dollar segmentation exercise.  At the completion of the segmentation project the organization had a set of statistically perfect groups of customers.  The groups were inventively and aptly named, full sample profiles of each group were generated, and beautiful charts were created that showed the different groups.

The organization had successfully segmented all of their customers into groups of like customer attributes.  The problem was that the marketing group had no way of using this information to improve customer retention, cross-sell and overall customer lifetime value.

They knew which customer was similar to which other customer but they weren’t able to determine a customer strategy from this information.

What they had discovered is that all the segmentation in the world is of no use to you if you don’t have a customer strategy that lets you know what action to take.

My preference is to approach the problem from the other direction.  Determine a good customer strategy (by individual customer) and then use segmentation to help you deliver the message.

We use a customer value based customer strategy approach called cpMAP.  Using this approach gives you a direct way to attribute a primary and secondary customer strategy to each individual customer.  Perhaps the strategy is primary cross-sell and secondary retention or perhaps it is primary retention and secondary product migration.

Customer Value Map

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Now that you know what to do with each customer you can use the segmentation to craft a treatment with the maximum impact.

For example, you’re primary strategy for this customer could be cross-sell of a credit card account.  You then use your segmentation to influence the creative, channel and timing to maximize cut through.  One customer may receive an outbound email with one creative followed up by an SMS, another may receive a different creative via the mail followed by a telephone contact.

With this approach you have a customer plan and you use the segmentation to maximize the effectiveness of that plan.  The segmentation is NOT the plan.

By Adam Ramshaw

Filed Under: Customer Analytics, Customer Strategy Tagged With: , , ,
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