This article’s title really intrigued me: Trust-Based Targeting.

Hmmm. Now, as a direct marketing and analytical specialist, I’m an expert in targeting. I’m aware of the wide array of data that is available to target both customers and prospects, B2B and B2C. So, what the heck does Trust-Based Targeting refer to? Clearly, I had to read more!

It’s an intriguing concept, and one that might actually help with the eventual measurement and better targeting of social media. The article outlines mEgo’s approach that allows consumers to choose the kinds of messaging and targeting behaviors that fit their own needs and interests, all in the area of social marketing.

The premise behind mEgo’s offering is that their users self-create some pretty elaborate and detailed profiles. Then, users decide which parts of their profiles can be shared to advertisers. Finally, users are paid (I believe through donations to their chosen charity) when advertisers use their data for targeting.

“Going back to how mEgo intends to roll out our advertising strategy: We will provide a transparent description of how users’ data is used and, most importantly, allow users to filter which information is publicly available and used for targeting. MEgo members will have complete control of what portions of their profile they’ll permit us to use to target ads. For example, a mEgo user interested in music may choose to view only ads for indie bands generated from a list of their favorite musicians. As an extra step in transparency, we also literally show users the keywords our platform generates for serving the ads they see.”

The article contained an excellent case study for an Adidas social media campaign. It illustrated the viral nature of m’Ego’s offering and is probably the best illustration of this new targeting concept.

I can’t wait to see how (if) other marketers adopt this model. I salivate over the rich data that I may be analyzing in the near future!

But I think that the key things to remember here are trust and transparency–two essentials to this new offering.

“The lesson learned: It is essential that brands earn and keep consumer’s trust in order to be able to effectively market to them. Without trust, the greatest marketing system in the world can’t work. Set the expectation of complete transparency between marketer and consumer, and you convert your consumer from being fearful into being an advocate.”

I really enjoyed a recent post I found on the Precision Marketing online magazine.  Jenny Hoffbrand  discusses Ian Ayres new book called Super Crunchers and a quote from the book that really summarizes the value of using analytics in the business, as opposed to relying on your “intuition” or gut-feeling: “Intuition and experiential expertise is losing out time and time again to number crunching. Businesses and governments are relying more and more on databases to guide their decisions.”

The post goes on to talk about Ayres recent keynote speech at the recent SPSS Directions Conference in Athens, Greece.  “Ayres used his platform at the conference to endorse the advancements being made in the field of predictive analytics and encouraged brand owners to use their data to determine the most suitable strategies for their marketing campaigns.”

Oftentimes, we see really savvy direct marketers get so tied up in the day-to-day that they forget the value of predictive analytics.  And, they go immediately to their gut feelings on what population to use in the upcoming direct mail campaign or what a certain segment consists of when they create their messaging.

And, time and time again, we see this “intuitive approach” fail.  Let’s face it — the smartest direct marketer in the world is probably not psychic.  We’ve seen very few direct marketers (actually none) who possess the ability to wave their hand over the server that houses their marketing database and pull out an “Ah — 45-65 years old, incomes of $100K+, with 1.3 children per household.”

I’m not bashing the customer intelligence that direct marketers obviously accrue over time, I’m simply emphasizing Ayres argument — that is when you dig into the data and analyze it scientifically you end up with a really robust — and highly accurate — idea of who your customers are, what segments may exist, who may be most responsive to your offerings, etc.

On the other hand, analytics isn’t all about number crunching either.  It’s about using the statistics to better mine the data, then using your business intelligence to look at the output and come to meaningful conclusions and recommendations on how to better conduct your direct marketing efforts.

That’s why there will always be a need for the creative process in direct marketing.  As Philip Keevill, creative director at Kitcatt Nohr Alexander Shaw, states: “If you get rid of intuition, you get rid of emotion. You can’t predict emotion with a machine.”

We agree with Hoffbrand . . . the two should be used together to create the best direct marketing strategy.

You know that we’re firm believers in using analytics for more effective direct marketing.  More folks are becoming believers along with us these days.  Why?  Because you’ve got to be able to measure the effectiveness of your direct marketing efforts.  Part of this is due to the increased scrutiny of marketing budgets but, I think, it’s more due to our evolution as marketers.  Let’s face it, if we can’t prove that what we’re doing works, sooner or later a change will come — and it may not be positive.

I’ve been reading a lot of articles on this topic, and today I found one that really resonated with me.  It’s by Neil Mason of ClickZ Network.  In his article, “Why the Planets are Aligned for Analytics,” Neil gives us his post-analysis of the recent eMetrics Marketing Optimization Summit in San Francisco:

The stage was set on the first day with a keynote presentation from author Tom Davenport on Competing with Analytics. “The planets are aligned for analytics,” he said, meaning that all the necessary components for organizations to adopt and deploy analytical capabilities are being put in place. Those components are: data, enterprise, leadership, targets, and analysts.

“Using analysis is good, competing on analysis is better,” summed up the need to be able to move from insight to action. There’s no point knowing stuff if you don’t do anything about it. He described the five stages of an organization’s analytics capability from being “analytical impaired” at the low end of the scale to being “analytical competitors” at the other end. Organizations, such as Harrah’s and Marriott in the U.S. and Tesco in the U.K., deploy analytics as a source of competitive advantage.

Every time we’ve worked with an organization who embraces our analytical approach, we’ve had astounding success.  On the other hand, when working with harried direct marketers who don’t take the time to close the loop with analytics, we’ve seen something very different occur . . . folks running around like chickens with their heads cut off being very reactive as opposed to proactive.

We preach the gospel according to analytics to each and every one of our valued clients.  And, we continue to be relentless on this topic because we have seen so much success from utilizing an analytical approach.  We’ll make them all converts yet!

Have a great week!

As analytical experts who often rely on external data to fuel our studies, and our clients’ marketing programs, we thought we’d share some results on data costs.

From Direct Magazine, check out this report on the price of data and leads. The article cites a Worldata study called “Winter 2008 List Price Index”, and it reports on changes in data costs year-over-year.

Very interesting stuff, especially if you need help in budgeting costs. Here are some highlights of the study:

• The cost for e-mail lists is decreasing slightly (by $2 per thousand, while consumer e-mail lists dropped by $3 per thousand).
• But e-mail lists still remain fairly pricey, at an average cost of $287 per thousand for permission-based B2B marketing and $135 per thousand for B2C permission e-mail.
• The average cost for Donor lists is $85 per thousand.
• Business Merchandise Buyer lists go for $118 per thousand while Consumer Merchandise Buyers average $103 per thousand.
• Consumer Magazine Subscriber list costs average $108 per thousand.

And, this quote from the Direct Magazine article should help you understand what to expect when you are buying lead data.

“Cost-per-lead data, which the Boca Raton, FL-based firm began tracking last quarter, had a slight increase in its pricing, due to jumps in B-to-B leads. Cost-per-lead consumer programs averaged $1.30 per lead, a slight decrease over last quarter, while cost-per-lead B-to-B Programs averaged $4.90 per lead, an increase of 7% over last quarter.”

Unfortunately, the study does not include average data costs for compiled data (such as consumer lists from Acxiom or Experian, or business lists from InfoUSA or D&B). Compiled data is definitely a less expensive option. And, Occupant lists (you know the direct mail that is not even addressed to a name, simply to “Occupant” or “Resident”) are even cheaper.

Still, this study gives great insight into what’s going on in the list/data industry and provides you with an educated guess as to data costs if you are budgeting a direct mail or e-mail campaign.

I came across this chart and remembered the fact that sometimes a picture is worth a thousand words.

So, if you have analytical expertise, you’re in good shape to ride out (and even thrive in) this crazy economy.

And, for more encouraging marketing news, check out this post from our Direct Marketing Blog. A little hint–marketing budgets don’t seem to be on the chopping block, even in this economy!

You know that we’re huge advocates of using statistical techniques to improve marketing performance. So, when I listened to Richard Sharp, VP of Marketing for Marqui speak on the topic of lead scoring at the Innotech e-marketing conference last month, I knew it would be a great session. Richard spoke about how important it is for marketing to qualify leads through an objective scoring system, prior to handing the right leads over to sales.

We couldn’t agree more and we decided to highlight a Marqui client success in today’s post. This success story comes directly from their sales literature.

Background and Client
Strangeloop Networks develops a family of network appliances designed to help businesses optimize the performance of their website or web-based application. Their business clients can then deliver new features and applications faster and at a lower cost without changes to software code or hardware infrastructure.

Challenges
Strangeloop Networks was a newly launched company that needed to hit the ground running. With limited marketing staff and budget, they still had to deliver enough sales-ready leads for their team. They had to transform their website from “brochure-ware” into an active lead generation component. They also had to create lead generation campaigns that could easily plug into their existing Salesforce CRM and Google Analytics web analytics package. They wanted a more effective means of evaluating their marketing programs instead of relying on conflicting anecdotal information from their sales team.

Solution
Strangeloop selected the Marqui Marketing Automation Suite, as it included key features and guaranteed a fast implementation. The Marqui Marketing Automation Suite provided both web content management and marketing campaign tools, offering a single-vendor solution. Total implementation time including training was only a few weeks before they were able to start running their first lead generation campaign.

Results

* Executed campaigns 3x faster
* Reduced budget for external contractors by $14,400 annually
* Increased conversion rate by 10% each onth
* Established automated workflow for managing and approving content
* Ability to track profitability of multi-channel campaigns

All in all, sounds pretty impressive! It’s great to see small businesses succeed by being clever, and by choosing the right technology.

Marketing Sherpa recently published this excellent case study on utilizing segmentation in e-marketing campaigns to grow lists and lift response rates — and all this in a time of economic downturn!

SUMMARY
An e-retailer has been using gender- and store-specific email promotions to lift revenue and grow their customer mailing list.

CHALLENGE
With consumers tightening their spending habits, many email marketers will be happy to see any kind of sales increase this year. James Connell, Senior Director for Ecommerce, Digital Marketing & New Media, Roots, a Canadian-based clothing multichannel retailer, realized late last year that his company might be affected, too. That’s why he and his team decided it was a perfect time to boost the relevancy of their emails.

“We needed to do a much better job of driving people to something that’s relevant,” Connell says. “I had been signing up for our competitors’ emails, and I had been getting mostly messages that didn’t apply to me. That was educational.”

Connell saw more relevancy as a competitive advantage their brand could pounce on. And with response rates dropping and consumer spending falling, he wanted to test some new ideas to optimize their email program.

Connell and his team were already following best practices on privacy and deliverability, but they were essentially sending the same offer to their whole email list over and over again. They knew the next step should be list segmentation … and time was of the essence because of the gloomy economic forecast.

CAMPAIGN
First, Connell began by identifying some key areas where they could improve email relevancy.

Three areas:
o Targeting women and men with gender-specific offers
o Segmenting email lists even further based on their 128 store locations
o Identifying which days of the week were best for email by testing *every* day — not just the industry-proven midweek days

Here are the five major tactics Connell and his team followed:

Tactic #1. Segment customer list by store location and gender
To deliver more targeted messages, Connell organized their list names into separate files according to store locations. They took the ZIP Code attached to each name from past online purchases and then assigned it to the closest store.

Then, he and his team divided the customer list even further into separate files for men and women. They manually went through their customer list to make the new files. For customers without distinctly male or female first names and purchase patterns, they created another file they labeled “undetermined.”

Tactic #2. Identify ‘un-determineds’
They didn’t stop with simply segmenting their customer list. Every ‘un-determined’ name was emailed a survey to get seven data points:
o Name
o Gender
o State/province
o Last purchase date at Roots.com
o Last purchase date in a Roots factory outlet store
o Favorite department
o If they were interested in Roots’ yoga department

The survey of “un-determineds” allowed Connell and his team to further segment their customer files by gender and their 124 Canadian and 4 US stores.

Tactic #3. Promote sign-ups at each store
The survey process also involved creating email sign-up forms for each store. New customers were offered the chance to win various prizes if they signed up. Store managers turned the names into Connell and his team by shop and city location.

Tactic #4. Create segmented offers
In the end, customers received both store- and gender-specific offers that involved printing out an email coupon (usually a discount on an item) to take to the nearby outlet.

• The copy pointed out that the offer was good not only online but also at their local Roots store.
• The address and a directions link were included to encourage redemption at the stores.

If a customer walked into the store without the email coupon but still mentioned the promotion, the stores gave them the same discount. Each store manager was responsible for reporting the number of redemptions back to Connell by phone or email after the promotion expired. There was no digitally computable coupon code.

Customers who were not within driving distance of the stores did not receive these offers. They were put into a separate online-only customer file. They received gender-specific offers that were designed to purely drive online sales.

Tactic #5. Test emailing *every* day of the week
Connell didn’t want to leave any money on the table by taking for granted the industry’s almost de facto ‘best days’ [Monday through Thursday] for emails. So, they tested every day of the week, including Saturday and Sunday.

RESULTS
Connell has no doubt that the segmentation tactics have increased the relevancy of the clothier’s email campaigns. At the same time, email-based sales have increased by 14% compared to the same period the year before.

“We’re happy to be getting a lift in these difficult economical times and expect the percent to continue to grow as we do more segmentation. We are seeing higher opens, click-throughs and better ROI. And because of the increased relevance, our emails get forwarded more often and we are increasing our subscriber base.”

Connell and his team grew their subscriber base by 22% during the first six weeks of the campaign with the in-store email component. “About half the stores have participated in the email promotions so far, and that number is increasing.”

They also saw “a steady 40%” completion rate of the surveys sent to clarify a customer’s gender and local store and they’ve been getting a 15% redemption rate for the email-exclusive offers as reported by the store managers.

Giving discounts to people who mentioned the email offer — without proof that they received an email — also appears to have been the right move. “We encourage email sign-ups in the store, so it makes sense to accept the promotions in that setting to help create more of a multi-channel identity.”

Connell couldn’t offer specific numbers on the best days for emails. But he says Tuesday and Wednesday proved to be their best send days. Still, team members were intrigued by the numbers they received on the Sunday tests.

“We are seeing surprisingly high click-throughs on Sunday emails. There’s a lag time in sends for that day where people open up and click on Monday and even Tuesday. With the click-throughs you see midweek, they happen very quickly or they don’t happen at all.”

It’s no secret that in this down economy direct marketers are continuing to find themselves under more and more pressure to do more with less — while at the same time continuing to deliver better results.

Recently, we were talking with a colleague about using more personalized communications when marketing to customers and prospects.  Our colleague, Michael Hurley, works for Imago Digital.  They use personalized marketing — and several forms of it — on their most successful direct marketing campaigns that they create for their clients.  It turns out that this is an excellent idea — you should see some of their response and conversion rates on these personalized campaigns.  They are through the roof when compared to traditional direct mail campaigns.

You may ask “why all the hub-bub on personalized communications?”  Well, to nobody’s surprise, personalized marketing is very customer-focused.  And, being customer-focused works!  In fact, there are many case studies that present success stories when utilizing personalized messaging.  The results of these studies are tied to huge increases in ROI on direct marketing campaigns.

We recommend taking this success to the next level by combining personalization with marketing analytics. And why not combine personalization with known attributes about your customers or prospects?  Doing so can grab hold of the recipient’s attention by communicating the most relevant message to the right groups of people.

There are a couple of ways to accomplish this. First, start out by profiling your customers to better understand what attributes that they possess that make them your customers.  You’ll end up with a good idea of exactly what your buyers look like.  Once you’ve accomplished this for your customers, look at a representative sample of folks who aren’t yet your customers and determine which of them look most like your buyers.  By targeting those prospects that most closely resemble your customers, you’ll be increasing your chances of turning prospects into customers.

Next, you can segment your customer universe to hone in on those groups that share certain characteristics, then design your messages to speak to those characteristics.  As seen in our previous post on creating effective segmentation plans, it’s amazing how effectively you can “speak” to your customers when you better understand who they are financially, ethnically, psychographically, etc.

So, as you are planning future campaigns, think about using personalization along with marketing analytics to really increase your results.  Over time, you’ll notice the profitability of your marketing efforts increasing, along with the products sold and lifetime value of your customer base.  This is a winning scenario that we promise will make you more successful!

You know you’re getting old when news doesn’t seem like news. You’ve heard it before. Same old story. Can you relate?

It’s certainly how I felt reading this story from DM News: Study says CMOs are failing to use CRM well.

“Marketers worldwide are under-utilizing data and analyt­ics, particularly when it comes to customer retention, according to a recent study released by the Chief Marketing Officer Council.

Only half of marketers have a strategy in place for growing key account relationships, and 45% believe CRM systems are not effective enough. Further, only 15% of companies rated them­selves extremely good or effective at integrating disparate customer data sources, and 6% of marketers reported having “excellent knowl­edge” of customer data such as demographics, psychographics or transactional history.”

The article goes on to talk about how so many companies continue to be focused on new customer acquisition and fall short in developing strategies designed to retain the customer.

In today’s environment of short-term gratification (we must meet sales goals THIS MONTH; we have to report favorable earnings THIS QUARTER), I tend to understand why a long-term, customer-centric strategy might fall by the wayside. Couple the need for immediate results with an ever-shrinking marketing staff and budget, and I start to wonder how any company can think strategically and look at long-term benefits.

But, here’s the kicker–this way of thinking with the customer in mind is a necessity. Customers today are aware of the data and technology that is available to corporations. They see it used to their advantage in their everyday dealings (the classic example is shopping with Amazon). They expect you to know all about them. They want you to anticipate their needs. They need you to serve them the right price plan or the right mix of products. If you won’t do it, you’re in danger of losing that customer.

It may be time to look at your customer touch-points and make sure that you’re doing all you can to keep those customers happy.

Following is a short-list of ideas that might jump-start the evaluation process:

• Have you empowered your call center or customer service folks to really assist customers calling in with issues? Are they able to make real fixes and solve problems?
• Do you have a handle on your customer relationships? Have you done the analysis and database work to understand exactly what products and services each customer is buying from you (or has purchased in the past)?
• Do you have a strategy in-place to make sure that you are maximizing the profit potential from each and every customer? Do you make the right up-sell and cross-sell offers, when the customer is most likely to be shopping?
• Conversely, do you have a strategy in place to ensure that you are not over-serving your customer? For example, are they on a price plan that is too big for their needs, hence they’re paying too much? Trust me, eventually, your customer will realize that they’ve been paying too much for your service, and they’ll leave you. To retain this customer and maximize their lifetime value, perhaps you should be pro-active and “right-size” their plan, before they do…

Luckily, we direct marketers, with our background and experience in data mining and using analytics to understand–and predict–customer behavior, are well-positioned to make a positive impact on customer marketing. Nancy and I have re-focused our direct marketing consulting practice to be centered on analytics and data. It’s that important, we believe.

Perhaps it’s time to become the customer advocate within your organization!

One of our pet peeves is unorganized, dirty customer data.  I know — we must lead very sad lives for this to be the case.

However, here’s the scenario we find again and again.  We’re helping a client plan their direct marketing strategy.  We ask them for a sample of their customer data.  We find that it is in such a terrible state of disarray that no one can make heads nor tails of it . . . arghhh!  Or, worse, they have a difficult time finding the actual “owner” of the database.  It can get messy!  But out of disarray comes opportunity — it’s the whole making lemonade out of lemons thing.

I’ve seen many articles lately stating that companies just aren’t getting the most from their customer data.  And, we’ve seen this to be quite true.  And most of the time it’s because of unorganized data.  However, the beauty of a dirty database is that there is such a wealth of opportunity waiting to be unlocked if you bring in an analytic approach.  And, you can start by mining your customer database and uncovering all of the elements that make your customers your customers. Data mining gives you the power to market to your customers more effectively — appealing to their needs and ultimately getting them to respond and buy.

Starting out with data exploration, you’ll begin to see common themes emerge that you never knew existed.  Mining your customer data provides you with the intelligence to set your direct marketing strategy, and really make your products and services appeal to your customers, which in turn, creates a stronger relationship with them.

So, the next time you think that your database is a mess and that you can’t get IT to give you the information that you need in order to conduct your direct marketing campaigns effectively, bring in the data miners.  Unleash them on your data (give us a call — it makes us happy to do this stuff!) and let them help you realize the gold nuggets that have been locked away in your customer database.  We promise that data mining will pay dividends in terms of customer loyalty and response.