Gaining Customer Attention is Step 1 in a Successful Email Campaign!

Continuing on the theme of last month’s post “Every Campaign Gain is a Win”,  let’s discuss incremental gains.   While measuring incremental revenue and profits is the bottom line, measuring incremental email opens and click through rate (CTR) is indicative of how well each wave of the campaign is performing.

Just looking at email metrics, a recent campaign showed a lift of 8% in Opens among existing customers.  What does that mean?  It means that 8% of the total universe of customers mailed in this wave engaged and opened the email although they had not done so in the prior wave.  Additionally, we saw a 2% incremental lift in CTR (click through rate.)

Even before we measure revenue and profit we know that we have impacted customer Attention!  And really, that’s half the battle.  Back in the day,  we spoke of the number of advertising impressions (number of times you’d see the same ad) needed to incent consumer trial.  That number was 9.   In my experience not much has changed to minimize the effectiveness of contact frequency, i.e., communication wave.  Frequency is one of the key variables that can be leveraged in a campaign strategy to create incremental gain.

Which is not to say that emails to customers should be too frequent.  There is an optimal number which you will have to find, but no one contests that upping email frequency drives revenue and profit. Check out the cool frequency diagram from the Mark Brownlow post, “Email Frequency: can you increase it safely?”

Hope I made you look!

Ann McCartan DBMCatalyst.com

Every Campaign Gain is a Win

We all set goals – email opens, email clicks, conversions, store visits, product purchases – for our marketing campaigns & programs. As we should! And typically those goals are high – 40% uplift, 20% incremental revenues or profits driven, 30% conversion. Many companies, especially when they are implementing more sophisticated techniques like multiple waves of communication or multi-channel initiatives, sometimes forget to factor in the type of audience they are addressing.

Consider a campaign to existing customers. If you are a service provider with loyal customers (those who have purchased from you repeatedly), you should look for modest gain. Hey, they already love you! Take the extra 2 – 3% gain over past campaigns and consider it well worth the effort. You’ve just retained a valuable customer who will continue to buy from you in the future. In one recent campaign, set to execute 4 communications to customers over 4 weeks, we’ve seen an 8% lift with just the first communication alone.

If you are looking for larger returns consider conducting an acquisition campaign. Those will typically drive higher returns with the right offer.

Remember that you are asking consumers to choose you and to trust that your product or service will provide ultimate benefit to them.  And remember that every campaign gain is a win.

Ann McCartan, DBMCatalyst

Comment Below to let me know what you think!

 

Let’s put the Data back in Database Marketing

In the last year I’ve had numerous opportunities to explain what I do…and explain and explain…mostly to people who are involved in some aspect of marketing but not database marketing specifically.  To a person, when I’ve said “database marketing” they’ve said “oh you work with computers (database.)”   Well, I do some of my work through a database but that’s not the essential point.   And then, as you can imagine, the conversation has veered off into technology….

Technology may be the enabler, and clearly the database is key, but the data are paramount.  Database marketing is about the collection and application of data – about the customer and the prospect.   Wikipedia, an eminently detailed reference describes it like this:  “…Database marketing emphasizes the use of statistical techniques to develop models of customer behavior, which are then used to select customers for communications…”  Data establishes the foundation and impetus for how companies go to market.  Complete and current data will translate into marketing intelligence needed to drive the right offers down the right channel at the time most preferred by the customer.   And that’s only possible by understanding consumer behaviors, attitudes and preferences – again the data.

The role of the database (computer) itself is to enable the collection and maintenance of that critical customer/prospect data and the generation of communications.  But that role is secondary.  It’s quite possible that the “data” has been lost in “database marketing.”  Do we need a new name?  In fact why don’t re rename the field to “pattern marketing” or “model marketing?”  Isn’t that a truer description of a field founded on models such as RFM?

So, let’s remember that both the data and technology are crucial, but the data drives business impact and profits….any other thoughts out there?

Please leave a comment

Regards, Ann McCartan, DBMCatalyst

Selecting the Right Marketing Program Metrics

As a quantitative market researcher – earlier in my career – I learned a couple of key lessons about research design which have held true as a direct/database marketer. Foremost, that you have to know what results you need, and what business decisions you need to make, before ever crafting a question. Call it a hypothesis, if you love science, or a set of decision points, if for business.

So, what does this have to do with selecting the right marketing metrics? I was reading a great article “E-Mail Metrics That Matter ” and, while the whole article is worth reading, what made it great was the assertion that before selecting any metrics, it is crucial to know “what business goals you are trying to attain and what problems you are trying to solve.”

This is really the point, isn’t it?  How can you measure the success of a marketing program without establishing its business purpose and the metrics to measure that?   I’ve seen many a post-campaign analysis that failed to answer the question “did my campaign achieve my business purpose?” because right success metrics were lacking.   Remember to ask:  what am I trying to achieve, how do measure success and what data will be available to me to use?

Read the article and take the time to craft a short brief prior to each and every campaign!

Best,  Ann McCartan, DBMCatalyst

Tell me what you think by leaving a comment, thanks.

If Your Marketing Automation budget got an extra $10,000, where would you spend it and why?

Recently I got into a conversation about incremental budget and basically how to optimize marketing automation with a shot of cash.

My reply was to spend the additional funds on improving the data, specifically, data enhancement. This is the addition or overlay of elements that describe the prospect or customer fully, such as demographics/firmographics, psychographics (attitudes, lifestyles) and most importantly behaviors. These elements are the basis for segmenting the consumer into groups such as best customers/prospects, most likely to upgrade or purchase additional products/services as well as for the creation of predictive models.

These elements enable the company to derive information (vs. data) about the consumer which in turn enhances targeting strategies – in my opinion, the key to profitable, incremental customer relationships.

Best,  Ann McCartan, DBMCatalyst

 

Retooled and back in business!

It’s been a while since I’ve posted my thoughts on marketing automation and database marketing. After a bit of retooling of my own Nuts & Bolts, I’m back and ready to resume sharing my insights and experiences. Look for more frequent and shorter communications as well as a new focus on customer information and analysis.

Best, Ann McCartan, DBMCatalyst

Building Customer Insight

I didn’t write the article I’m going to present, but I could have.  Which is not to compare or detract from Joseph M. DeCosmo’s wonderfully concise “survey course” in using customer insights to target relevant messages to the most receptive customers or prospects.  The Goal: make money from your customer data, right?

I could have written it because I have experienced every step along the path he describes both as an employee of or consultant to large corporations who have decided that customer data is the key to relevant marketing.   In his article, “Building Customer Insight“  (you may have to subscribe to access it), DeCosmo presents the following steps:

1. take a comprehensive inventory of customer data  -  consider ALL the systems where information about your customer may reside
2. take a hard look at the quality and quantity of each source/each element
3. start by building a profile of customers
4. segment customers into different commonsense groups
5. use a simple cross tabulation analysis to compare ad contrast the different segments
6. model the customer lifecycle – as it relates to each of your product lines and overall
7. measure and model lifetime value – again by product line and overall
8. add primary customer research to flesh out the modes and profiles
9. now that you know who to market to and why….you can create meaningful,  relevant communications

Naturally there is much more detail to each step, but the framework is so practical and logical it’s almost a recipe for great database marketing. Enjoy!

Ann McCartan, DBMCatalyst

Let me know what you think by leaving a comment

Customer Loyalty – Are We Overlooking a Key Factor?

Do we really understand what drives a customer’s loyalty?  How often is customer service measured and factored into the “loyalty” equation, as well as the calculation of a customer’s life time value?

Today I read a post  “A lesson from LeBron James for loyalty marketers” cautioning brands to remember that today’s program offerings, promotions and selections – though inspiring multiple purchases and trips – may become less relevant to customers tomorrow.  In short, loyalty ain’t what it used to be and and marketers need to be ever vigilant to changes in customer profiles that indicate swings in a competitor’s direction. If you can detect when customers’ loyalty shifts, you’re ahead of the game.

I also came across a story about “Retail Banks Making Less From Customers” which reported on a decrease in customer loyalty and a caution that “…..consumers…..will move away from institutions that provide poor customer service…”  This reinforced my longstanding belief that loyalty is more strongly influenced by interactions with the company customer service staff or store associates or in-home technical services than by the marketing “4Ps.”

Let me demonstrate what led to my conviction.   At a large, regional cable & broadband company, we began to model tenure (loyalty) and lifetime value (LTV.)  At that time, we believed that customer satisfaction was strongly correlated to customer tenure.  We regularly polled our customers to monitor and measure their satisfaction with products, price and efficacy of all our customer-facing departments.  What we found was that the strongest correlation to tenure and LTV was between the number and nature of “trouble calls”, i.e., service interactions, and customers’ tenure.

Regardless the number of product lines purchased – and clearly enjoyed – by customers, their satisfaction across the board declined if the number of service interactions increased.  Pushing further into the data it was found that among a wide range of types of service interactions, “trouble calls” proved the most problematic.

Specifically, the data illustrated a trend among those who had an increasing number of “trouble calls” to downgrade services and in some cases attrite, even when other entertainment options were limited.  By creating a score for customer service frequency and volume we created a trackable variable.

We were able to add this variable to predictive models for downgrade and attrition/churn as well as to the lifetime value calculation for cable & broadband customers.  We were then able to tie customer loyalty and tenure, hence lifetime value, to pre-emptive improvements in customer service.  In the end, this proved to be more important to their continued loyalty.  As marketers, we could move forward with not only the best product and promotions but the knowledge that our customers’ were receiving the best possible experience from all customer-facing groups to enhance their experience with the company.

Regards, Ann McCartan, DBMCatalyst

Let me know what you think by leaving a comment!

B2B Segmentation – Which are the relevant behaviors?

Just the other day in my post,  “Digging Into Customer Behavior” , I listed some of the behaviors that appear to indicate strong purchase intent or seriousness and also mentioned that each one can have a different impact depending on the true interest of the Visitor.

So, which of the behaviors is indicative of an intent to Convert?  How do you assign importance or ranking?

Behaviors such as attending Webinars, downloading White Papers, Site Surfing and Contact Requests are all observed behavior but not always clear indications of intent to purchase.  For example, what is the value of a White Paper Download?  Some companies require contact information as a prerequisite for the download, while others believe the papers should be freely given?  I hate to tell you the number of calls I’ve received after providing my company information to download!!!  In fact I had no intention to purchase, I was just curious.

How does a company determine the overall importance of any one particular behavior or set of behaviors?  What about the time element, i.e., certain behaviors over time?

What are the relevant behaviors in your industry or company?  How do you measure them?

Do leave a comment or if you like email your comment in private to:    ann@dbmcatalyst.com

Cordially, Ann McCartan,  DBMCatalyst

B2B Marketing – Digging Into Customer Behaviors, Segmentation and Three Top Benefits

I’ve recently read about new trends in B2B Marketing:  the use of behavioral analytics, psychographic segmentation and data overlays.   (B2B Magazine, “Transformation via Sophistication” ) There’s no doubt that behavioral tracking and analysis shines a light on the pathways that lead from research to interest to engagement and on to conversion.  The trick is understanding which activities most strongly correlate to the ultimate conversion process and how to move the prospective buyer from point A to point “C.”   And when to disengage from prospects, i.e., Visitors, who endlessly participate in downloads, webinars and even frequent site click throughs without any intention of purchase.  The cost to maintain interaction with “Visitor” isn’t insignificant.

Will certain behaviors indicate a higher propensity to convert?  Can you Clone them?  Absolutely, but a relevant segmentation model might be more predictive.  In the B2C world, segmentation is often based on purchase recency, frequency and amount spent, RFM.  The assumption is that customers who have purchased recently are in the “buying” mode and can be easily incented to make another purchase.  Or that frequency is a measure of willingness to spend.   This isn’t entirely relevant to B2B where purchases may simply be larger and purchased less frequently due to their shelf life.  Or due to inherent budget cycles.  What does apply however is the concept of “best” customers designated by the purchase volume, number of products purchased, number of lines purchased and frequency of purchase throughout the year.

Whether deciphering behavior or segmenting customers into deciles, quintiles or quartiles the process allows for 3 Immediate Benefits to occur:

1. Cloning – by association with best customers transactional, on and off-line behavioral, and possibly by their psychographic profiles, certain prospects or customers can be demonstrated to be more potentially valuable than others.
2. Marketing Resource Allocation – budgets and resources (people, process and technology) can be allocated appropriately to each segment/behavioral profile.
3. Behavior Modification – by understanding best customer behaviors, marketing tactics and programs can be calibrated to move prospects, customers and other browsers towards the appropriate destinations – Visitor, Long and Short term Converters.

There is going to be much more to talk about as this B2C approach becomes wholly adopted by B2C Marketers.    Leave a comment and tell me what you think!

Ann McCartan, DBMCatalyst