5 Tips for Faster, More Confident, Direct Marketing Budget Decisions

As we enter the critical make-or-break fourth quarter, and you begin your 2014 direct marketing budget plans, you will likely be faced with many marketing decisions. Those decisions are usually needed quickly. But often they’re not made quickly. Whether it’s information overload from so many options, analysis paralysis or managers who are afraid to make a decision, today we explore five ways to

As we enter the critical make-or-break fourth quarter, and you begin your 2014 direct marketing budget plans, you will likely be faced with many marketing decisions. Those decisions are usually needed quickly. But often they’re not made quickly. Whether it’s information overload from so many options, analysis paralysis or managers who are afraid to make a decision, today we explore five ways to make marketing decisions quicker and more confidently.

A mere generation ago, direct marketing decisions were limited to direct mail customer file or rented lists, space ads in magazines, package inserts, direct response broadcast, and a few other media options.

Fast forward to now, and the direct marketing decision landscape has grown exponentially with online and cross-promotional media options. Every season reveals new, unexplored online opportunities. Some are fads. Some turn out to have real value.

So for your direct marketing budget planning, here are five recommendations of how to evaluate opportunities and make decisions more quickly and confidently.

1. Cost per Response
An important metric for most direct marketers is the marketing cost per response (per lead, inquiry, sale—whatever your situation). This core metric may be your most significant contributor to your decisions.

2. Allocation of Unknown Response Sources
If you’re in a situation where you have a significant number of responses for which you can’t pinpoint a specific marketing source, consider a weighted-average allocation of those responses across marketing activities. With some imagination, you should be able to calculate this on your own. (Let me know if you’d like an expansion of this concept, and perhaps we’ll do so in a future blog post.)

3. Summarize Results in a Matrix
Placing your data in a spreadsheet will put the numbers in front of you so you can see all your activity in one place. You may want the data by media type on separate spreadsheet tabs so you can see more granular data.

For example, on one tab you summarize results from direct mail (by list, or summed up by customer vs. rented lists) with cost per response. If you allocated unknown orders, be sure to include those. Another tab might concern email results that summarize opens, clicks, conversions and cost per response. Other tabs could summarize pay-per-click, social media, retargeting or whatever media you are using. Then roll up and summarize all of the media on a tab of its own. If cost per response is most important to you, then sort the data from the lowest cost per response to highest. Perhaps you have “soft data” that will be a factor in your decisions. If so, add columns to enable a written evaluation of each. Maybe your evaluation is as simple as “pluses” and “minuses” for each opportunity.

4. Parameters for Decisions
It happens all the time. With so many choices and options, and potentially several staff members wanting their piece of the budget, decisions can be contentious and slow. When that happens, everyone loses. When you establish the parameters for decision making upfront, it’s easier to slice the pie into the right proportions. More importantly, if the head of the organization or department has established those parameters in writing (avoid verbal direction to avoid future misunderstanding), staff is empowered to make more confident decisions without delay.

5. Don’t Forget Test Budgets
Know, ahead of time, how much money you can gamble in a test. You should view the money spent as having zero return so that when if it works you’re pleasantly surprised. A rule of thumb you might use is to allocate 10 percent of a total marketing budget to tests. Whether it’s a direct mail list test, or new online media, the only way you can learn if those options work for you is to test it. Remember, too, that marketing fads can fizzle quickly. The hot new opportunity of 2012—not even a full year ago—may already be a distant memory.

If you have processes, or recommendations, about how you make faster, more confident marketing decisions, please share them in the comments area below.

A New Way to Net B-to-B Services Sales With Social Trust

Oh no … not another article on how important building trust is with social marketing. Please I can’t take it anymore! I admit we hear too much hype about the importance of trust but behind all the blather there’s a powerful new approach emerging in B-to-B services sales forces. This is the exact system you should be using to exploit social marketing programs that tap LinkedIn, blogging, Twitter, video, etc.

Oh no … not another article on how important building trust is with social marketing. Please, I can’t take it anymore! I admit we hear too much hype about the importance of trust, but behind all the blather there’s a powerful new approach emerging in B-to-B services sales forces.

This is the exact system you should be using to exploit social marketing programs that tap LinkedIn, blogging, Twitter, video, etc.

This foundational method has traditional roots. It’s based on what works—amplifying concepts that have always worked. It’s just re-tweaking them for our hyper-networked, always-on world.

A Buyer’s Decision Model
Selling B-to-B services in the past looked like this. It’s a selling process:

  1. Lead qualification
  2. Presentation
  3. Objection management
  4. Close
  5. Buyer’s remorse (sometimes!)

The new buyer-focused decision model (forced upon us by the Internet) looks like this:

  1. Cognitive thinking
  2. Information gathering
  3. Divergent thinking
  4. Convergent thinking
  5. Evaluation

For years now we’ve been hearing “it’s not about how we are selling, it’s about how customers go about buying.”

Well duh! Realizing this means nothing. Acting is everything. Building practical B-to-B social marketing strategies that create leads and sales is a must. That’s what this post is all about.

From Messenger to Trusted Advisor
A buying decision model is different than a selling process. Herein lies the emergence of an entirely new industry that hot new companies ranging from point-of-sale messaging firms like Corporate Visions to software-based lead generation companies like HubSpot are set to exploit.

So what’s in it for you and your brand?

In his book, “Putting the Win Back in Your Sales,” Samurai Business Group’s, Dan Kreutzer reveals this decision-making model and quickly elaborates on putting it to use.

“This model provides a framework for how buyers make decisions and, ultimately, how sales people can build trust by helping buyers make effective buying decisions,” says Kreutzer, a 25-year veteran of building winning sales organizations on an international scale.

Think about that for a minute. As social marketers, what if our job is actually less about messages and email “blasts” and more about guidance and education? In this context the buyer decision-making model comes into clear focus.

Social marketing suddenly makes more sense.

What If?
What if you could bring marketing and sales together by helping customers:

  • Engage in critical thinking and situational analysis—placing less strategic emphasis on qualifying leads and coming up with killer content marketing messaging?
  • Move toward or away from your services—gaining confidence in decisions they’re making thanks the trusted, needed advice we provide.
  • Determine ‘best fit’ by publishing powerful (“transparent”) and overtly honest truths—helping customers evaluate all options available to them through useful decision-making tools and education.

What if “the doing of” all these things resulted in creative, effective brand messaging, better quality leads and shorter sales cycles? Well they already are for some organizations.

In weeks ahead I’ll be profiling companies and diving deeper into the subject of using this B-to-B buyer-side model to make social media sell for you.

What do you think?

MDM: Big Data-Slayer

There’s quite a bit of talk about Big Data these days across the Web … it’s the meme that just won’t quit. The reasons why are pretty obvious. Besides a catchy name, Big Data is a real issue faced by virtually every firm in business today. But what’s frequently lost in the shuffle is the fact that Big Data is the problem, not the solution. Big Data is what marketers are facing—mountains of unstructured data accumulating on servers and in stacks, across various SaaS tools, in spreadsheets and everywhere else you look in the firm and on the cloud.

There’s quite a bit of talk about Big Data these days across the Web … it’s the meme that just won’t quit. The reasons why are pretty obvious. Besides a catchy name, Big Data is a real issue faced by virtually every firm in business today.

But what’s frequently lost in the shuffle is the fact that Big Data is the problem, not the solution. Big Data is what marketers are facing—mountains of unstructured data accumulating on servers and in stacks, across various SaaS tools, in spreadsheets and everywhere else you look in the firm and on the cloud. In fact, the actual definition of Big Data is simply a data set that has grown so large it becomes awkward or impossible to work with, or make sense out of, using standard database management tools and techniques.

The solution to the Big Data problem is to implement a system that collects and sifts through those mountains of unstructured data from different buckets across the organization, combines them together into one coherent framework, and shares this business intelligence with different business units, all of which have varying delivery needs, mandates, technologies and KPIs. Needless to say, it’s not an easy task.

The usual refrain most firms chirp about when it comes to tackling Big Data is a bold plan to hire a team of data scientists—essentially a bunch of database administrators or statisticians who have the technical skills to sift through the Xs and 0s and make sense out of them.

This approach is wrong, however, as it misses the forest for the trees. Sure, having the right technology team is essential to long-term success in the data game. But truth be told, if you’re going to go to battle against the Big Data hydra, you need a much more formidable weapon in your arsenal. Your organization needs a Master Data Management (MDM) strategy in order to succeed.

A concept still unknown to many marketers, MDM comprises a set of tools and processes that manage an organization’s information on a macro scale. Essentially, MDM’s objective is to provide processes for collecting, aggregating, matching, consolidating, quality-assuring and distributing data throughout the organization to ensure consistency and control in the ongoing maintenance and application use of this information. No, I didn’t make up that definition myself. Thanks, Wikipedia.

The reason why the let’s-bring-in-the-developers approach is wrong is that it gets it backwards. Having consulted in this space for quite some time, I can tell you that technology is one of the least important pieces in the puzzle when it comes to implementing a successful MDM strategy.

In fact, listing out priorities when it comes to MDM, I put technology far to the end of the decision-tree, after Vision, Scope, Data Governance, Workflow/Process, and definition of Business Unit Needs. As such, besides the CTO or CIO, IT staff should not be brought in until after many preliminary decisions have been made. To support this view, I suggest you read John Radcliffe’s groundbreaking ‘The Seven Building Blocks of MDM: A Framework for Success‘ published by Gartner in 2007. If you haven’t read it yet and you’re interested in MDM, I suggest taking a look. Look up for an excellent chart from it.

You see, Radcliffe places MDM Technology Infrastructure near the end of the process, following Vision, Strategy, Governance and Processes. The crux of the argument is that technology decisions cannot be made until the overall strategy has been mapped out.

The rationale is that at a high-level, MDM architecture can be structured in different ways depending on the underlying business it is supporting. Ultimately, this is what will drive the technology decisions. Once the important strategic decisions have been made, a firm can then bring in the development staff and pull the trigger on any one of a growing number of technology providers’ solutions.

At the end of 2011, Gartner put out an excellent report on the Magic Quadrant for Master Data Management of Customer Data Solutions. This detailed paper identified solutions by IBM, Oracle (Siebel) and Informatica as the clear-cut industry leaders, with SAP, Tibco, DataFlux and VisionWare receiving honorable mention. Though these solutions vary in capability, cost and other factors, I think it’s safe to say that they all present a safe and robust platform for any company that wishes to implement an MDM solution, as all boast strong technology, brand and financial resources, not to mention thousands of MDM customers already on board.

Interestingly, regarding technology there’s been an ongoing debate about whether MDM should be single-domain or multi-domain—a “domain” being a framework for data consolidation. This is important because MDM requires that records be merged or linked together, usually necessitating some kind of master data format as a reference. The diversity of the data sets that are being combined together, as well as the format (or formats) of data outputs required, both drive this decision-making methodology.

For companies selling products, a product-specific approach is usually called for that features a data framework built around product attributes, while on the other hand service businesses tend to gravitate toward a customer-specific architecture. Following that logic, an MDM for a supply chain database would contain records aligned to supplier attributes.

While it is most certainly true that MDM solutions are architected differently for different types of firms, I find the debate to be a red herring. On that note, a fantastic article by my colleague Steve Jones in the UK dispels the entire single-versus-multi domain debate altogether. I agree wholeheartedly with Jones in that, by definition, an MDM is by an MDM regardless of scope. The breadth of data covered is simply a decision that needs to be made by the governance team when the project is in the planning stages—well before a single dollar has been spent on IT equipment or resources. If anything, this reality serves to strengthen the hypothesis of this piece, which is that vision more technology drives the MDM implementation process.

Now, of course, an organization may discover that it’s simply not feasible (or desirable) to combine together customer, product and supplier information in one centralized place, and in one master format. But it’s important to keep in mind that the stated goal of any MDM solution is to make sense out of and standardize the organization’s data—and that’s it.

Of course there’s much more I can cover on this topic, but I realize this is a lot to chew on, so I I’ll end this post here.

Has your firm implemented, or are you in the process of implementing, an MDM solution? If so, what process did you follow, and what solution did you decide upon? I’d love to hear about it, so please let me know in your comments.