My Latest Research: Marketing Beyond The Status Quo April 23, 2008Posted by Elana Anderson in Customer Analytics, Customer Experience, Database Marketing, Integrated Marketing, Marketing, Marketing Technology, Online Marketing.
Tags: Balanced Scorecard, Marketing Relevance, Responsys
I am very excited to announce the launch of my latest research, “Marketing Beyond The Status Quo.” The research, sponsored by my friends at Responsys, seeks to help marketing organizations assess and address the barriers that prevent them from being more customer-focused, relevant, and integrated. The report unveils the Marketing Status Quo (MSQ) Model – backed by a diagnostic self-test and step-by-step program guide – to help marketers determine their relevance maturity and develop a realistic action plan to become more customer-focused.
The MSQ Model assesses the fundamental competencies required for marketing relevance:
- Strategic: How customer-focused are your marketing efforts?
- Analytical:How strategic and actionable is your customer insight?
- Technical: How well-suited is your infrastructure to support customer-focused marketing?
- Process: How collaborative, efficient and error-free are your marketing operations?
Each competency is equally weighted and combined to yield an overall Relevance Maturity Score, which defines a MSQ Level ranging from 1 (broadcast) to 5 (integrated). Marketers can leverage the model in conjunction with the MSQ Self-Test to assess their status quo, as well as identify the steps they must take in order to successfully move to the next level.
For a free copy of the full report, visit www.responsys.com/beyond. I hope that you will find the research interesting and the tools useful. If you have any feedback, please don’t hesitate to comment here or contact me directly.
See you in LA next week? April 1, 2008Posted by Elana Anderson in Customer Analytics, Customer Experience, Database Marketing, Integrated Marketing, Marketing, Marketing Measurement, Marketing Strategy, Marketing Technology, Online Marketing.
Tags: Forrester Marketing Forum, Intrawest, relevant marketing, Responsys
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Busy, busy, busy! That’s the month of April for me. Sorry I haven’t been posting the last couple of weeks, but I have a ton of balls in the air at the moment. One of the major things I’ve been working on is a minor treatise aimed to help marketers systematically improve the relevance of their customer communications. My work on this whitepaper, “Marketing Beyond The Status Quo,” is sponsored by the good people at Responsys and we’re planning to unveil it together next week at Forrester’s Marketing Forum in Los Angeles. Our session is Tuesday, April 8th at 2:25pm. I’ll be presenting along with Scott Olrich (Responsys’ CMO) and Randy Cuff (Director of CRM Development at Intrawest). Here’s the abstract for the session:
Few interactive marketers are ecstatic about their ability to deliver meaningful and timely marketing messages. In fact, most agree that more relevant and timely marketing communications will be better received by customers and increase response rates. However, when time is scarce, budgets are tight, and single channel campaign management solutions are already integrated and delivering ROI, marketers are hard pressed to change the status quo. In this thought-provoking session, Elana Anderson, former Vice President and Research Director leading Forrester’s marketing practice, and Scott Olrich, CMO of Responsys will unveil the findings from a first-ever study identifying the drivers of the “status quo” paradigm, and reveal the strategies and marketing technologies smart marketers are using to deliver superior marketing performance and ROI across channels.
If you are attending the forum, please stop by our session. I’ll be there for the full two days, so drop me an email if you want to connect at some point during the event. Hope to see you there!
CPM Pricing Will Ultimately Put EMSPs Out Of Business March 5, 2008Posted by Elana Anderson in Customer Analytics, Database Marketing, Marketing, Marketing Technology, Web Analytics.
Tags: Bronto, CPM rates, Email Marketing, marketing database, segmentation, targeting
After my tirade yesterday against volume-based CPM pricing in the email marketing sector, I was disappointed to see the recent post on Bronto’s blog announcing the vendor’s move towards a volume-based pricing model:
For the last five years, we have priced our clients’ subscriptions by the number of the contacts stored in the application (i.e., list size.) This worked great in the early days because we primarily had small business-to-business customers. As we grew and our business and product became more sophisticated, we attracted more sophisticated clients that send at higher volumes. Since list size mattered less and sending capacity mattered more to them, the model became tougher to match with our clients’ needs and trickier to manage operationally.
My perspective? This may be a way to be competitive in the short term, but ultimately it will put the email service providers (EMSPs) out of business. Simply put, it makes the EMSP nothing more than what I have long referred to as a “dumb pipe” – a platform for bulk pushing out messages. Despite the economic challenges I addressed in my previous post, most (to use Bronto’s words) “sophisticated clients that send at high volumes” are actively working to improve their ability to target and customize their marketing communications in order to increase relevance. As I also noted, this requires tools and the necessary skills to understand and leverage customer data. If the email provider doesn’t provide these tools and services, you can be sure that other providers will be there to fill the gap. Carpe diem.
CPM Pricing Is To Blame For Bad eMail Marketing March 4, 2008Posted by Elana Anderson in Customer Analytics, Database Marketing, Marketing Technology, Online Marketing.
Tags: Campaign ROI, Cheetahmail, CPM rates, e-Dialog, Email Marketing, Epsilon, Responsys
One of the issues I am currently working on is to understand what it takes email marketers to move beyond “fire and forget” (or “batch n’blast”, whatevah) marketing. I find that while marketers intellectually agree that more targeted, timely, and relevant email communications will be better received by customers and increase response, basic economics is a major barrier to progress in that direction. Why? Because email marketing is so darn cheap that every campaign delivers ROI – even if the campaign is totally untargeted (You ever wonder why spammers still spam? They make money doing it).
Relevance Isn’t Free
I’ve spoken with a few dozen email marketing leads from large companies and strong brands in recent months. Their hearts and minds are in the right place. Broadly speaking, they:
- Are concerned about opt-outs, unsubscribes, and long-term engagement with their email programs.
- View email as a tool to develop customer relationships.
- Are working hard to employ tactics – like multi-layer targeting, segmentation, and event triggers – to improve the relevance of their communications.
Unfortunately, as these marketers strive to improve their email communications, they inevitably run into a series of challenges including:
- Availability of timely, high quality data
- Access to skills that know how to turn data into actionable information
- Operational knowhow to automate data-driven processes
Wait… I’ve heard these problems before! In the 1990′s, when I worked with catalogers, financial services firms, and telcos to build some of the first big database marketing environments. Interactive marketers today sound just like big direct mail marketers did then.
Unfortunately, for the interactive marketing folks, the similarities stop there… Even though the highest percentage of upside from a marketing database typically derives from new streams of revenue, direct mail is so expensive that the mailers can justify a marketing database and a top-notch analytics team to help manage costs. Unfortunately, since email marketing is so cheap, interactive marketers can’t make the same argument.
Email Marketing Grew Up Out Of Advertising, Not Direct Marketing
Email CPM (cost per message) pricing was borne out of mass advertising which has historically focused on how many eyeballs see a message. Take a huge list, send the same message to everyone, and pay volume pricing – the more you send, the cheaper it is. OK – perhaps this made sense in 1997 when email marketing was a novelty but, let’s be honest, this pricing model is totally out of whack with how marketers want, and need, to leverage email today.
- Access to a richer dataset.
- Tools that support data slicing/dicing and more granular targeting.
- Improved campaign design and management functionality like event detection, rule- based dynamic content and dialog campaigns, and improved campaign automation.
But, as these vendors work diligently to provide their clients with the tools that they need to deliver targeted, timely, and relevant communications, they consistently struggle with downward pressure on CPM rates (which, today, are fractions of a penny per message). Last week I spoke with the CEO of a leading EMSP who told me that no matter what pricing elements they propose, prospects consistently turn the pricing into a CPM calculation to compare competitive vendors.
The Cost Of Relevance
While I am all for generating healthy competition amongst vendors, companies need to understand that boosting the relevance and sophistication of their email programs comes at a cost. What are the major cost components?
- Analytic data mart: A “data sandbox” that provides an area to explore data, profile subscribers, analyze behavior, and identify key pieces of data that can be leveraged to increase the success of your email programs.
- Analytics team: You have a sandbox, you need people that know how to play in it, develop business hypotheses, predict results, etc.
- Marketing database: Different from the analytic sandbox, this operational marketing database is a simplified data structure and only incorporates the data required to define, execute, manage, and measure current email programs.
- Campaign management and automation tools: These tools sit atop the marketing database. Marketing users (or service provider staff) leverage the tools to define, automate, and execute campaigns.
Recognize that all of the things I note above can vary dramatically in cost and scope and can be achieved in different ways:
- In partnership with an email service provider.
- In partnership with other providers (e.g., database marketing services providers like Merkle or Epsilon).
- If you have the in house skills, internally in your own shop with support from your IT group.
- A combination of the above.
Which way to proceed depends on a number of factors that I will be happy to address in future posts. But, the key point is… If you don’t do these things somewhere, you will not be able to improve the relevance and sophistication of your email programs.
Is eMail Doomed As A High Quality Relationship Marketing Channel?
Ultimately, I am trying to help email marketers build a business that will help them increase the revenues and longevity of the email channel. That case requires investment in improved data capture, data integration and management, and data analysis capabilities – all of which cost money. Email marketing specialists with deep knowledge of the channel are in a great position to offer these capabilities, but these vendors are stymied by CPM pricing. What will it take to truly move email marketing beyond its position as just another “mass advertising” channel?
It is URGENT that you give us a call… February 8, 2008Posted by Elana Anderson in Customer Analytics, Customer Experience, Customer Experience Hall of Fame -- and Shame, Database Marketing, Marketing, Marketing Technology.
Tags: credit card marketing, Do Not Call, FTC, marketing segmentation, robot marketing, SPAM, targeted marketing, telemarketing
Have you noticed an uptick in the number of robot marketing messages that you are getting? I have and it’s making me crazy! For the last several years I have worked from my home office 2-4 days a week. In recent months, the number of calls that I am getting with robot marketing messages has increased dramatically.
Some of the messages are “transactional.” For instance, we get calls from Blockbuster reminding us that we have an overdue movie. But most of the messages are pure marketing. Yes, my phone number is on the DNC list, but these calls are coming from firms with whom I have a “preexisting relationship.” The company I bought my car from, financial services firms I deal with, etc. The most egregious, from my perspective, are the messages that come from my credit card company which go something like this:
Hello, this is Amy from your credit card company! Now, nothing is wrong with your card, but it is URGENT that you contact us immediately to discuss how you can lower your monthly interest rate….
The first of these messages came just after my wallet was stolen last spring (see my post on that descent into customer experience hell). What did I hear? “URGENT that you contact us!” I like to think that I’m a reasonably intelligent person but I must admit that it took me a second to realize I was listening to a pitch, not a customer service call.
It may be legal, but it’s the worst kind of spam
As a marketer, perhaps you’re wondering what’s wrong with this. I’ll tell you. For me as an individual, these messages are highly interruptive, irrelevant, and unwanted — not to mention misleading. If this came to me as an email, I could delete it without a second thought. It would be a little annoying but not annoying enough to write this post. These calls require that I pick up the phone and listen. They take more of my time and attention and they make me mad!
I am not debating that these calls reach some people that probably consider a lower interest rate to be a very good thing. But, if my credit company bothered to do a very easy query against its customer databsae before teeing up these calls, it would see that I pay off my bill every month and don’t pay finance charges. Therefore, the interest rate is totally meaningless to me. For a company that I know employs fleets of statisticians and has very sophisticated customer analysis, I find this absolutely inexcusable!
Be responsible with this technology
I’m not suggesting that you never use this tactic to reach your customers. I am suggesting that you recognize that the phone channel is one of the most interruptive of channels (just shy of door-to-door sales) and if you choose to implement these automated phone campaigns you need to make sure that you are properly targeting your calls. Some suggestions:
- Don’t use “preexisting relationship” as carte blanche to call. While it may be legal, there are customers out there that just don’t want the calls, period. I recommend filtering contacts that have registered for the DNC list out of the call list particularly if your list isn’t well targeted to customers for whom the message is clearly relevant.
- Use data to target the campaign. If you have good customer analysis and response modeling capabilities then, by all means, use them. Even if you don’t, use basic queries to filter the list in order to screen out those customers for whom the message is obviously irrelevant. If you don’t have this capability, then you should not be running these campaigns.
- Be more genuine in the communication. If you are properly targeting the message, then you can make a more genuine appeal to your customer. Rather than, “it’s urgent that you contact us!” empathize with the customer by saying something like, “we notice that you have been paying high finance charges over the last few months and we want to offer you the opportunity to lower your rate for the next three months…” If I ever do get in a situation in which I am carrying a monthly balance, then this kind of offer would come in handy and I would feel like my credit card company was on my side.
- Be transparent with Caller ID. I failed to mention above that the calls don’t even have proper Caller ID (most say “unidentified number”). Although the FTC requires that telemarketing calls have proper Caller ID, apparently the rule does not extend to marketing phone calls where a “prior relationship” exists. I believe marketers should take the high road nonetheless and give customers the opportunity to screen the calls.
Demonstrating The Brand Value Of Email January 29, 2008Posted by Elana Anderson in Customer Analytics, Database Marketing, Marketing Measurement, Marketing Strategy, Online Marketing.
Tags: Control Group Testing, E-LOAN, Email Marketing, Interactive Marketing, Responsys, Test and Measurement
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I had the opportunity to catch up with Robert Raines, VP of Product Management & Creative Services at E-LOAN last week. I first met Robert several years ago when he was getting the company’s email programs off the ground. Robert shared with me some of the things that he’s accomplished since we last spoke and, as always, he had some great insights.
E-LOAN wanted to evaluate the impact of its email program
Robert is a firm believer in testing and, more specifically, using control groups to measure the impact of email marketing activities. To determine the long-term benefit of its email program, the E-LOAN team created a randomly selected universal control group. While the control group still received transactional email communications (e.g., ”We have received your application”), it received no email marketing treatment whatsoever for a period of 18 months.
To ensure that individuals selected into the control group were excluded from all email marketing efforts, the team created an exclusion table in its marketing database and automatically excluded the control group from any database extracts that were sent to its email service provider (Responsys).
What E-LOAN learned
What was E-LOAN looking for? The company wanted to evaluate the application rate of the mailed population vs. that of the unmailed population (the control group) over an 18-month period. As you might expect, at the beginning of the test there was very little difference in the application rate of the two groups. But, over time, the emailed population had a significantly higher application rate. So much higher that, according to Robert, the difference alone is enough to justify the total annual cost of the company’s email program.
Robert is also quick to point out that it’s not just about being in the inbox that matters. The E-LOAN team works hard to ensure that its email program is relevant and it uses a mixed strategy that includes broadcast messages (e.g., “The Fed has lowered interest rates”) and highly targeted, event-triggered communications.
Email marketers often complain that they don’t have enough staff and struggle to manage what’s already on their plate given the staff that they have. I believe that this complaint becomes a self-fulfilling prophecy… Email is cheap, just blast it out, and we’ll keep the bare bones operation going… To break through this cycle, email marketing managers should:
Devote 6-8 hours of the team’s time to implementing a test and measurement strategy. As a manager myself, I know that it’s possible to squeeze some amount of extra time out of the week. If you are really committed to making email marketing more strategic in your company, find 15-20% of someone’s time and focus it on test and measurement as Robert has done at E-LOAN. Sure, the E-LOAN test that I’ve shared here took 18 months, so start with something smaller. For instance, test the difference between a broadcast newsletter and a newsletter with dynamically targeted content.
Trend results over time. A quick test to show that targeted content generates higher open and click rates is indeed interesting. But, it’s more interesting to trend this information over time to evaluate the sustained value of a targeted vs. untargeted program.
Document a business case. If your goal is to improve the internal stature of your email efforts, get more budget, and grow your team, then it’s imperative to document your case. Avoid doing this at an individual campaign level and comparing metrics — like opens and clicks — against industry averages. Focus on the bigger picture and build a case that exposes the real business value of your efforts. What is the ROI of targeted vs. broadcast communications? Or, as in the E-LOAN example, do your customers buy more if they receive email marketing communications from you? This is the kind of case that your bosses need to free up more resources.
Tags: Acxiom, Coremetrics, Interwoven, Kefta, Offermatica, Omniture, Optimost, TouchClarity, Unica, Visual Sciences
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In my post just before the holidays, I shared a framework to help marketers think about how web analytics contributes to data-driven marketing effectiveness over time. Marketers agree that they want to deliver more relevant and timely communications, establish a two-way dialog, and generally be more customer-focused and integrated, but many are struggling to make positive progress. Use the framework to understand understand the maturity of your data-driven marketing practices. Then define your objectives and timeframe for making incremental progress. In this post, I want to discuss how marketers can use their placement on the framework to define the key requirements for their web analytics tools. I work with an awful lot of firms out there that are not getting the benefits that they should be out of the technologies that they purchase. Why? Well, I think one key reason is that they are overly aggressive in their expectations of what they will achieve and over what time. The result is a lot of wasted technology — and wasted time.
If we were more realistic about what we are trying to achieve (i.e., the business outcome) with our web analytics tools then I believe our learning curve around how to effectively understand and leverage the data would actually accelerate. Why? Because we wouldn’t be constantly struggling with the technology. The free tools on the market are getting better and, while they are not sufficient for marketers that are beyond Stage 1 maturity, they will meet the needs of many. Here is a starting point to help you get beyond vendor eye candy and align functional requirements with business objectives:
Stage 1: Site analysis
Key questions you need to address:
- How many visitors are coming to my site?
- How are visitors using my site?
- How are visitors finding my site?
Core functional requirements:
- Visitor analysis
- Referrer analysis (pages and keywords)
- Strong library of parameterized “out of the box” reports
Comments on the market: These capabilities are table stakes to enter the web analytics market and most of the solutions out there do a reasonably good job here. Expect a more limited library of reports and more limited customization features from the free tools.
Stage 2: Site optimization
Key questions you need to address:
- How can I increase site visibility?
- How do content and taxonomy influence desired action?
- What would improve site navigation?
Core functional requirements:
- Path analysis
- Page and scenario drilldown analysis
- Drop-off analysis
- A/B and multivariate testing
Comments on the market: This is currently an area of focus for leading vendors in the market. The once-standalone optimization players – like Offermatica (acquired by Omniture), Kefta (acquired by Acxiom), and Optimost (acquired by Interwoven) – have been acquired and other vendors are looking to add these capabilities through acquisition or organic development. Given current client emphasis on customer experience management, expect this to continue to be an area of hot competition in the near future.
Stage 3: Segment targeting
Key questions you need to address:
- How can I logically group site visitors?
- How can I target visitor content by segment?
- How can I leverage site learning in other communication?
Core functional requirements:
- Segmentation model templates
- Ability to persist segments
- Ability to create dynamic segments and apply them historically
Comments on the market: Leading web analytics vendors like Coremetrics, Omniture, Unica, and Visual Sciences (acquired by Omniture) offer segmentation capabilities but this is an area where vendors differentiate.
Stage 4: Individual customization
Key questions you need to address:
- What is the best content for an individual based on prior site interaction?
- Should I reach out to an individual customer NOW?
Core functional requirements:
- Individual visitor profiles retained over time
- Ability to match profile to current visitor context – in real-time
- Ability to unify profiles when visitor identifies
Comments on the market: A few leading vendors are really just starting to focus here. Omniture’s recent acquisition of TouchClarity is a good example. Unica is also working on integrating it’s web analytics and campaign management modules in a meaningful way. But, overall, the vendors are just getting started at figuring this out.
Stage 4: Integrated marketing
Key questions you need to address:
- How are customers using online and offline channels in the buying process?
- How can I optimize online and offline interactions?
Core functional requirements:
- Calculate and retain key profile metrics
- Track metrics longitudinally
- Open data model and facilitation of extracts to other systems
Comments on the market: Today, you’re mostly at the mercy of your internal IT shop when it comes to the level of data integration sophistication required to help marketers in large companies integrate their activities across channels. Some firms call upon their interactive agency, systems integrator, or database marketing service provider to help. But, each approach has its challenges. It may make you feel better to know that no one has nailed this one and that gives us all something to aspire towards. At the end of the day, I believe that if the web analytics vendors want to be part of the solution then they need to hire (or partner) with database marketing gurus in order to make real progress.
Web Analytics Needs To Grow Up (Web analytics series, Part 1) December 11, 2007Posted by Elana Anderson in Customer Analytics, Customer Experience, Database Marketing, Integrated Marketing, Marketing, Marketing Measurement, Marketing Technology, Online Marketing, Web Analytics.
Tags: Unica, Web Analytics, Web data analysis, Web maturity
Last week I was privileged to spend the day in the company of several thought leaders in the field of Web Analytics. Dr. Alan Hall, Avinash Kaushik, Judah Phillips, and I participated in several taped panel sessions that focused on how to best leverage web data to improve marketing effectiveness and how to effectively leverage investments in web analytics technology. We were joined by, Steve O’Brien, Akin Arikan, and Karen Hudgins from Unica which sponsored the get together. What struck me most about our conversations (on camera and off) is how committed each of us is to moving Web analytics beyond what today is largely a passive, report-centric discipline towards one that:
- Improves the effectiveness of individual customer interactions
- Actively contributes to the understanding of the customer
- Is a key part of improving marketing’s ability to measure across channels
Five key stages of web analytics maturity
One of the bits of original thinking that I contributed to the discussion was a framework that breaks down five stages of Web Analytics maturity.
Don’t pay attention to the stages for the moment… This is not a new picture (I pulled the base graphic from a from a client deck I presented in 1998). And, few would disagree. If a marketer is not leveraging any data to drive marketing communications, just adding a little bit of filtering or segmentation will have a tremendous positive impact on results. But, at some point, our ability to continuously improve results through segmentation levels off. At that point, the way to get the next hockey stick impact on results is to use individual customer data. Definitely not new thinking, but I think it helps level set us that is what “1:1″ or “customer-centric” (you pick the cliché) marketing is all about – using knowledge about the individual customer to drive interactions that, at the end of the day, benefit both parties.
This framework can also help us think about how we are using the mountains of web data that we’re collecting to help us move up and right on the chart. I break the role and the progression of web analytics down into five stages:
- Stage 1 – Site analysis: When we get started, we’re really just trying to get our arms around the data and the traffic on our site. The focus is to understand how visitors are getting to the site and what they’re doing there. But you also need understand why they’re there and whether they were able to accomplish what they set out to do. How do you do that? Avinash suggests that’s quite simple, ask.
- Stage 2 – Site optimization: The goal, of course, is to avoid analysis paralysis and look for ways to leverage the insight we are gaining about how visitors access and use the site to drive more visitors to the site, to optimize the experience of visitors once they are on the site, and to help more visitors accomplish what they were trying to do.
- Stage 3 – Segment targeting: As we continue to focus on improving customer experience, we inevitably start to look for ways to segment visitors into different groups either through data explicitly provided by the visitor or through insight inferred from the session and prior interaction data. We then apply the segmentation to customize visit experiences and target content.
- Stage 4 – Individual customization: At some point, our ability to continually apply finer segmentation and impact results levels off. That’s when we start to apply individual-level web interaction data to customize online interactions.
- Stage 5 – Integrated marketing: Of course, the holy grail of all of this is fully integrated and customer-centric marketing in which we seek to integrate insight from online behavior with what we know of an individual across other channels. And, we do this in order to inform and optimize all interactions – regardless of channel – with the individual.
The sad part of all of this is that few companies have matured their Web analytics capabilities beyond Stage 3. In fact, I’d estimate that 80% (not based on a quantitative study!) of firms are at Stage 1 or 2. Why? Well, it’s darn hard! There’s tons of data to wade through, the industry is learning as it goes, and the technologies that help marketers move up the curve are still pretty immature and poorly integrated.
So, how will this framework help?
Use the framework to understand where you are today and what you want to work towards and over what time frame. Each stage of maturity focuses on unique business objectives, requires a different level of analytical savvy, and demands different functional capabilities from your supporting marketing technology.
Over the next several weeks, I will continue to drill down on this topic with additional posts. Please add to the discussion by commenting and providing feedback on the blog or feel free to contact me directly.
Five steps to understanding customer retention December 4, 2007Posted by Elana Anderson in Customer Analytics, Database Marketing, Marketing, Marketing Measurement, Marketing Strategy.
Tags: customer profitability, customer retention, retention rate
I recently responded to a question from a network that I participate in.
What is achievable customer retention and is there a level of customer retention that is not profitable to reach?
I’ve talked with a lot of marketers about this question and, frankly, there is no easy bake answer. It’s easy to look for a quick published statistic or benchmark and call it a day. But, how much does knowing that your retention rate is better than your competitor’s really help your business? It may help CYA, but it doesn’t help your bottom line.
IMO: marketers rely way too much on benchmarks (open rates, click rates, retention, etc.). Rather than rely on industry benchmarks (I don’t even know of a comprehensive source for retention by industry), I encourage marketers to:
- Establish a baseline for current average retention. Examine your customer base to understand average retention. Better yet, do it by customer segment if you can.
- Understand the timeline to customer profitability. Every business has different acquisition and services costs so if you don’t already know how long it takes for a new customer to become profitable, then you need to figure it out. Subtract your costs to acquire and serve the customer from average customer revenue over time. Companies that are really good at this use individual customer revenue and get into cost minutia to attribute costs at an individual level and even include costs like physical plant and electricity. But, if you’re just getting started, keep it simple and stick with averages.
- Set a target retention rate. The longer it takes to become profitable, the higher the retention rate needs to be. Establishing and monitoring a retention KPI will tie retention directly to business performance.
- Define marketing tactics to improve retention. If current retention is not at the target level, then set improving retention as a key business objective and drill down into a series of tactics aimed at moving the needle. Don’t shoot in the dark though. Engage a statistician to do some data analysis to better understand what key factors that correlate to longtime customers or customers that attrite. Then, establish marketing and customer service practices and campaigns that are specifically focus on encouraging the factors that are correlated with long-term customers.
- Measure results consistently. Periodically, reevaluate the retention rate to see how what you are doing is impacting customer retention. Make sure you are also considering metrics that help you tweak your programs at a tactical level too. Specifically, are the tactics you have implementing really encouraging those factors that correlate with long-term customers?