Head in the Cloud? The one time “MORE” is really not.

I think we all like to receive things – especially unexpected things. Like when you receive that unexpected gift from your significant other for no reason at all. Or when you find a twenty-dollar bill in the parking lot a the mall. Or when you get an unexpected raise (even though you probably deserved it). More is better, right?

How about when you discover several free (or really inexpensive) cloud connectors that perform a variety of interesting functions. Everyone needs clean data, so why not really clean it up with several plugins or cloud connectors? Or what about appending data, since you probably need addresses and phone numbers anyway. Free? More is better, right? Well, maybe not in this case. Let’s look at a few reasons why not.

Free is not Free
This is the most obvious (and easiest to understand) reason you may want to investigate a little deeper. Check to make sure the free cloud connector or plugin does not require a paid subscription service to actually use it. It should be fairly simple to determine the process required to obtain value from the connector, so make sure that surprise isn’t an unpleasant one.

The Results are not Useful

Going back to previous {Demand Gen Brief} posts, we saw that first identifying your business problem is the key to understanding how to solve for it. For example, while data appending cloud connectors can be useful, make sure the field values are what you need. For example, if your target audience is regional warehouse managers, data that appends the headquarters address and phone number is not going to be particularly useful. Compound that statement for international organizations, where a HQ address might get you in hot water for emailing to a recipient who actually lives and works in a tightly regulated country.

The Results Conflict with Each Other

This requires a bit more investigation and requires you to fully understand your root business problem. What happens when you extract the phone number from one service and the address from another and the two services use very different methodologies for obtaining (or curating) their data. You may find area codes and zip codes in conflict with one another and your logic programs are unable to determine the real location for that company.

Speed Concerns

As we saw in an earlier post, some cloud connectors and plugins have imitations on processing speeds or volumes. These need to be carefully considered when included in programs like Contact “Washing Machines” that function in-line in your lead management processes. If you have lead delivery SLAs, make sure you are not implementing cloud connector processes that take longer that your SLA allows!

Change the conversation.

When it comes to cloud connectors and plugins, free is not always better. More is not always better. Finding the correct level of processing is always the best solution. Only address real problems with solutions that directly solve them. Partial solutions or mismatched combinations of solutions may well leave you in a worse condition than where you started.

Notes:

You need to first understand your business problems.

Fully understand what each cloud connector or plugin actually does.

Make sure any cloud connector actually solved your business problem.

At the end of the day, you need to understand how your Demand Gen efforts are contributing to the bottom line. We will begin a four-part series to understand what you should be working towards, some serious question you should be asking and a common problem to avoid in: Four Ways you are Marketing Backwards.

Head in the Cloud? Three ways to evaluate cloud connectors.

There seems to be a plugin or a cloud connector to do just about anything. Match data, clean data, import data, export data, add data to the data you already have, brew an espresso… OK, maybe not brew an espresso, but most certainly everything else.

In fact, they all sound so great and they cost so little, why not just get them all? As we just read, getting them all could definitely create some conflicts in your database and, while each serve a particular purpose, their purposes might not match your purposes! So, how do you go about selecting the plugins and cloud connectors best suited to your purposes? Let’s look at three ways you can evaluate the best approach to implementing one or more that will solve – not exacerbate – your problems.

Mind the Gap
Your selection of plugins or cloud connectors should be initiated by functional gaps in your lead management process. If you don’t know of any functional gaps, you have either a) the world’s one and only perfect lead management process or, b) not performed a lead management (or lead lifecycle) analysis. There are a few questions you need to answer when mapping your lead management process, and these will guide you to understanding the gaps (usually informational gaps) in your process.

·       Do I completely understand my Total Addressable Market (TAM)?

·       Do I understand all the buyer types and their individual buyers’ journeys?

·       Do I have all the information I need to properly segment my audience?

·       Do I have all the information I need to mechanically score my contacts?

·       Do I have all the information I need to properly route leads where they need to go?

If you don’t’ have complete answers and the data to support those answers, you have discovered your gaps.

Identify your options

If you have an information gap in your lead management process, chances are good others have similar challenges. Where challenges exist, bright people have often identified solutions to those challenges and create cool solutions. Many of these solutions are in the form of cloud connectors and plugins you can easily install in your MAP or CRM platform.

Do some research and identify a list of solutions and the companies who created them. Then use social media to perform some initial discovery about how well your peers have fared using them. Go beyond feature/function comparison to see how well the overall solution performs in real world application. Check for the company’s responsiveness in dealing with installation and service calls. Make sure the solution can meet your speed requirements, especially if you have lead timing SLAs with your Telequal or Sales teams (cloud connectors can be slow). Make a list of requirements and make sure the solution can meet those – or surpass them!

Pilot your solution

Many of your potential solutions will offer some kind of free trial or evaluation period. If not, ask the sales rep to allow for one. Within a thirty-day test period, you will have identified whether or not the proposed solution is a solution or just another headache. Create a small test group of contacts in your MAP representative of the information gaps you commonly experience.

A good way to do that is to take a cut of your data with a fairly random factor, such as one thousand contacts with first names beginning with the latter “J.” Create copies of these contacts, substituting test email addresses and names, such as First1, Last1 and test1@ACMEtestcontacts.com. If you can store these in a Contact Group or similar method of isolation, it makes it easy to delete these contacts after your pilot.

Change the conversation.

This methodology works for virtually all plugin and cloud connector solutions you may want to deploy. By aligning the solutions to the problems, vetting vendors and piloting your solutions, you will get where you need to go without creating additional problems along the way.

Notes:

You need to first understand your process gaps.

Systematically vet potential solution providers.

Pilot your solutions.

Next, we want to understand one of the specific issues you need to avoid. Many plugins and cloud connectors have to balance the need to create solutions with broad appeal to offset the inexpensive cost of cloud-based solutions. This can often translate into a bit of a one-size-fits-all structure that creates unnecessary system overhead: Head in the Cloud? The one time “MORE” is really not.

Head in the Cloud? Why more plugins and cloud connectors may be making your problem even worse!

Think of the last visit to your doctor. Did you drag your tired, nauseous self into the exam room, plop down on that table with the funny roll of paper and have your doctor immediately proclaim, “I think you’ll need major surgery” before even examining you? Would you maybe ask her to use that stethoscope and those little tongue depressor thingies to perform some basic diagnostics first? Maybe an X-ray or CT scan might be in order before calling in the scalpels? How about a second opinion, doc?

Or how about your car? When you wheel in for your 25,000-mile service, what would you think of your mechanic who says, “Whew! That car’s maroon – it’s going to need a new engine. And new wiper blades.” Would you just keep right on driving until you found a mechanic with the proper diagnostic equipment to evaluate what – if anything – needs adjustment? Of course you would!

While we would never subject our bodies or our vehicles to such ridiculous treatment, it seems we are happy to turn over our Marketing databases and MAP platforms to exactly this kind of treatment! Cloud connectors and plugins seem like such great solutions to problems, they are just irresistible. They are, for the most part, inexpensive, easy to install and run without any human intervention required. What’s not to like about them? Here are a few things to think about.

They mask the real problem
Like taking ibuprofen to reduce a fever when the real problem is an infection that needs treatment before your immune system can no longer battle on its own. If left untreated, the infection can kill you while the ibuprofen artificially reduces the fever your body was using to fight the infection. Likewise, cloud connectors can treat problems to an extent.

Bad data? Get a cloud connector to clean it up. Can’t segment? Get another cloud connector to standardize your data. Need physical addresses? Get yet another cloud connector to pull in addresses based on the browser’s IP address.

Sounds like a great solution to – what was the problem again? Oh, yeah, bad data. And by “bad” I mean incomplete, non-standardized or incorrect data.

They can limit your options

Because they are inexpensive (or sometimes free), cloud connectors and plugins can have standards to which you will have to comply. For example, if you segment geographically by Congressional Districts instead of Area Code, or have a unique target audience that doesn’t use the “standard” organization levels of Manager, Director, VP (etc.), you may be out of luck. The more sophisticated your segmentation, the less likely cloud connectors will completely address your root problem.

They process at different speeds

You may find you have to make accommodations for the speed and/or volume of cloud connector processing. Many have limitations on the number of Contacts processed per unit time, require longer processing cycles than you might expect, or both. Understanding what kind of throughput you require is critical when determining whether or not cloud connector or plugins are a viable solution for you.

What should you consider?

First, you need identify the problem from a business perspective. These are Demand Generation and Lead Lifecycle problems, not technical problems. These problems follow a formula, and are easily identified:

A to B by when

For example:

I need to promote our new widget to every medical practice with more than 30 employees  in the state of Florida before April 30^th.

Now that you have identified the business problem, you to perform some diagnostics to determine the reasons why you can’t promote your widget to your target audience. The root cause (diagnosis) will help determine how you will solve that problem (treatment). Let’s look at some potential examples of root problems.

1.     You don’t’ have any medical practices in your database. Those cloud connectors may polish up the data in your MAP only to find out that you have nicely standardized and appended a database not in your target market. Your still have not solved your business problem.

2.     You don’t have geographic information on your contacts. Many organizations try to append this data via cloud connectors or plugins that extract address information from either company names or IP addresses. These can produce spotty results if the company headquarters is in another state or in another country. Fi you are marketing to a medical practice in Pensacola, but the headquarters is in Poughkeepsie, your automated programs  may inadvertently skip right over that prime prospect!

3.     Your title segmentation is incomplete and inconsistent. That cloud connector or plugin is looking for some title to rationalize to “Director” or “VP” and Dr. Sarah Jones – the actual director of your target medical practice – has a title of “Physician.” Your database now thinks nobody is in charge of your prime target medical practice.

Change the conversation.

Don’t misunderstand, I believe cloud connectors and plugins are a good thing.  They have good application when applied to the right problem. They are, however, not a magic bullet for every business problem and, in fact, can actually make your root problem worse!

Notes:

You need to first understand your business problem.

You need a proper diagnosis to determine the solution.

Not every problem can be solved with a standard solutions, cloud-based or otherwise.

Next week, we will continue the discussion about cloud connectors and plugins. Now that we know we need to really understand our business problem before prescribing a technical solution, we will investigate how to determine if a cloud connector is a viable solution in next week’s edition: Head in the Clouds? Three ways to evaluate cloud connectors.

Three Ways A-B Testing Will Improve Your Marketing. (Part 3) Into the Vortex.

Automating your Demand Generation functions is often referred to as a journey. However, your journey need not be aimless and without a destination. In fact, if you don’t have a destination in mind, your journey will take much longer then necessary and, in fact, may never end. As the saying goes, “If you don’t know where you’re going, how will you know when you get there?”

While your ultimate destination may be something like “a world-class Demand Center,” you will need to establish some milestones along the way to measure your progress. Testing will help you to establish your progress toward (and beyond) those milestones. When it relates specifically to A-B testing, there are some great milestones against which you should always be measuring your progress! Those milestones may be found in your Demand Waterfall (or Demand Funnel).

Principle #1: Programs should be measured against movement
Marketers often fall into the trap of trying to generate activity. Activity is fine, but if that activity does not result in movement, it has both cost you money and gained you nothing. Let me explain.

Let’s say you create an outbound marketing program, sending 50,000 emails to your target audience. You have written incredibly compelling content with a CTA pointing to a wildly popular whitepaper. Your Subject Line drew a 50% open rate and your content prompted 50% of the opens to download your fabulous whitepaper, resulting in 12,500 downloads at a 25% conversion rate. My guess is you’d be jumping up and down at your success after posting these metrics. Not so fast! You’ve generated lots of activity, but have you generated any movement?

Unless you got paid for all of those whitepaper downloads, you’ve actually spent time and money to send out a free piece of information to your prospects, customer and, likely, your competitors. Here’s the real question: what did the recipients do as a result of reading the whitepaper? What was the goal of your program? Was it awareness, engagement or conversion? Did the readers react according to your goals?

Principle #2: Movement should be measured in terms of Waterfall Stages

You have a Demand Waterfall for a reason, which is to determine your prospects’ stage in their buyers’ journeys. Assuming your Waterfall accurately reflects that buyer’s journey, each and every program you deploy should have the specific purpose of moving the prospect from one stage to the next in the funnel.

In our previous example, let’s assume our whitepaper program was an engagement program, with the purpose of moving Inquiries to AQL (Automation Qualified Lead) stage. Based on this goal, we now have a movement objective against which we can measure the success of our program. We can determine the success or failure of the program in terms of how many Inquiries convert to AQLs as a results of the program.

Principle #3: Movement should indicate a significant interaction with your brand

Is downloading the whitepaper enough to indicate a significant interaction? Just because a reader downloaded it does not guarantee he or she even read it. How many downloads do you have just sitting on your hard drive waiting to be read at some future date? We can differentiate between insignificant and significant by creating a definition for those actions.

An insignificant interaction is a download with no continuation of the interaction. Sometimes I download something simply because I want the information and somebody has offered it for free. I have absolutely no intention of purchasing anything, but the information seems interesting or useful.

A significant interaction is a download with a continuing action. For example, a well-designed program might have a secondary CTA within the downloaded asset, prompting readers to engage more deeply with your brand. As an example, after reading mare about a specific A-B Testing solution, another CTA could prompt the reader to try a free testing tool or interact with a free testing framework generator. This continuation action would indicate the reader’s real interest in your solutions.

How do we measure movement?

Waterfall movement is a matter of understanding changes to a Contact record in your MAP. This change has a number of components you need to understand in the context of many other potential changes simultaneously affecting that same Contact record. So how do you isolate the movement you need to measure? The first priority is to make sure you are capturing the required data behind the metrics you want to measure!

1.     You should systematically link your Waterfall program to your response measurement. There are a variety of ways to do this; the goal is to attribute Waterfall movement to a specific response – almost always the most recent significant interaction. This is different from Campaign attribution, in which most organizations want to attribute closed revenue across all campaigns that touched the Contact during the Lead lifecycle.

2.     You need to record your program responses so they are actionable by your Waterfall program. This means you will not only need to understand which program, but when the Contact responded.

3.     In most cases, you will also need to record how the Contact arrived at the program CTA in order to convert. This is a great basis for testing which routes to the CTA are most effective.

Change the conversation.

Optimization should be conducted with the program movement goal in mind. If we go back to our original whitepaper marketing program, we would likely make significant changes to the way we determine success if our goal is Inquiry-to-AQL conversion. IN that case, 12,500 whitepaper downloads that don’t result in AQL conversion might look like a tactical success, but is actually a strategic failure. How would we change the conversation?

First, we would change our target audience to include only Contacts in the Inquiry stage. If the goal is to convert Inquiries to AQLs, what is the purpose of sending to any other than Inquiries? Second, we would insure our infrastructure was pre-built to capture the data points necessary to measure Inquiry-to-AQL conversion. There is no sense setting a goal we cannot measure. Thirdly, we set up our A-B testing points to measure the things we can both control and change, such as traffic sources. Did outbound emails work better than banner ads, or did paid SEM work better than purchased media?

Notes:

Testing must be performed with an overall objective in mind.

You should be testing movement, not activity.

Your infrastructure must be pre-built to capture the data necessary to your metrics.

Next week, we will take a look at how your MAP platform might be doing a whole lot of processing that accomplishes nothing. With SaaS and cloud-based solutions come a plethora of cloud-based add-ons. They do all sorts of nifty stuff, but do you really need or want them? Maybe, but there is a right and wrong way to look at cloud connectors and plug-ins. We will look at them in next week’s edition: Head in the Clouds? Why Less may be More.

Three Ways A-B Testing Will Improve Your Marketing. (Part 2) Avoid Misdirected Testing.

Last week we decided that any testing framework needed to have a specific destination in mind – your objective.  While it is reasonably straightforward to match your testing framework to your overall Marketing objectives, it is easy to get misdirected and lose track of your destination.

If your car has a GPS navigation system and if you’re anything like me (I always have a better route), you have heard that voice in the GPS say, “Turn around at the nearest U-turn!” Repeatedly. Mindlessly. Until you just turn it off. (Or, in my case, the GPS finally gives up, decides I’m right, and recalibrates the new course.) You’re A-B testing framework should be like that voice in the GPS, incessantly reminding you that you have left the prescribed course. How? Here are some guidelines to help you understand when your testing is off-course.

Guideline #1: A-B test results are not extensible and repeatable
Subject Line testing often falls into this category. If your testing is not extensible and repeatable, the test is only applicable to that particular email. To repeat a lesson we learned in {Demand Gen Brief} last week, categories of tests, rather than specific tests should be used like this:

We would apply scientific method to create a series of hypotheses to test these assumptions to ultimately create a rule by which all future subject lines are created, such as:

1.     Subject lines should be less than 35 characters.

2.     Subject Lines should include our company name.

3.     Subject Lines should contain the recipient’s first name.

Guideline #2: A-B tests are not actionable

What’s the point of performing a test if you can’t action the results? An example of such a test would be to perform an A-B test on CTA button colors only to find that purple wins by a landslide. Problem? Purple is your main competitor’s color and your brand standards prohibit its use in any way. There are, however, some very interesting takes on this guideline. For example, “best practices” are to not use some key words in your subject line, because they can trigger email client SPAM filters. Or not. What if 50% of your emails got sent to SPAM filters because you used the word free in the subject line, but the remaining 50% showed a 1200% open rate increase over the next best subject line? Would you break “best practices” and go with free? Of course you would, unless…

Guideline #3: A-B tests are specific to only one part of the equation

Remember, each test in your framework is designed to test a specific metric, and each metric measures only a part of the journey from Prospect to Closed/Won. In the previous example, using the word free in the subject line increased your open rates by 1200%. Great, but what happened next? Did those opens turn into clicks? Did those clicks turn into MQLs, SQLs and, ultimately closed business? Your testing framework should be looking at the entire lead lifecycle to determine how each action contributes to the progress of the entire demand funnel. Let’s look at another example.

Open                    Clicks                       Convert to MQL                   Convert to SQL                   Closed/Won

1200x.5=600      .01x600=6               .50x6=3                                  .5x3=1.5                               .5x1.5=.075

100                       100x.25=25            .50x25=12.5                          .5x12.5=6.25                        6.25x.5=3.125

In the end, that great open rate using the word free only resulted in opens, not clicks. Using the exact same conversion rates from MQL through close, we find a 400% improvement in closed business not using the word free in the subject line.

Change the conversation.

Again, A-B testing must be performed within a holistic framework that considers the entire demand funnel and what each tested step contributes to the whole. Unless you get paid for people opening your emails, the 1200% increase in open rates does not serve your organization’s overall objectives.

Notes:

Testing must be performed within an overall framework with a specific objective in mind.

Testing must consider both the specific action being tested and its overall contribution towards the overall objective.

Again, “best practices” for company A are not necessarily best practices for company B.

Next week, we’ll look at how to tie your testing framework to demand funnel progression, and why it is critical to build your framework that way: Three Ways A-B Testing Will Improve Your Marketing. (Part 2) Into the Vortex.

Three Ways A-B Testing Will Improve Your Marketing. (Part 1)

The old Chinese proverb says. “A trip of a thousand miles begins with a single step.” While I’m still not sure how the ancient Chinese knew anything about English units of measure, the saying does imply something very important: a destination. A trip of a thousand miles invariably leads somewhere. And that somewhere is likely missing from you’re a-B testing.

If your testing framework is only that, a testing framework, you are missing out on one of the key benefits of testing. You should be testing with a destination in mind: optimization. Your goal is to both optimize current campaign performance and do it in such a way you can apply that optimization to future campaigns. Let’s look at an example of the types of A-B testing I’ve seen.

Test #1: A-B email Subject Line testing
You may have performed this type of testing, so you know how it goes. This is an open rate test, and is critical, since nobody can respond to your CTA if they don’t open the email first. You take otherwise identical emails and test one subject line against the other, such as:

1. ACME sells really keen widgets
2. ACME widgets solve all the world’s problems

You split off 10% of your campaign segment and send Subject Line 1 to half that audience and Subject Line 2 to the other half. Whichever Subject Line wins the test gets applied to the other 90% of the segment, assuming the open rates will follow the same pattern as the test.

Test #2: Email CTA link testing

Once the recipient opens your email, the next critical step is to obtain a response to your CTA. A number of tests have been employed here, such as:

1. Change the color of the link button – red vs. blue
2. Move the button to different spots on the page – right column vs. inline
3. Use different graphic elements as a button – arrow vs. rectangle

The test is run in exactly the same manner as the Subject Line test, with the winner of the pilot group getting sent to the remainder of the segment.

So, what’s wrong with these tests?

Nothing is wrong with the tests themselves. What’s wrong is they are not performed within a framework aimed at solving the real problem. Let’s start by asking this question: How much does your organization get paid when someone opens an email? How about when they click through from an email? (Unless you are a PPC organization those business model is built on creating click-throughs.) For the vast majority of B2B organizations, the answer is $0. We get paid when someone engages with our sales team and ultimately buys our products or services. So what should our optimization framework ultimately measure?

Tactically, we should think of open rate optimization in terms of “best principles” (there’s that term again) we can apply against all of our tactics to improve our funnel conversion rates and velocity. In our Subject Line test, will we actually use that identical Subject Line in another program to the same segment next month? I hope not. Therefore, we need to think of our optimization framework as a series of repeatable principles that we can employ in all subject lines. We would apply scientific method to create a series of hypotheses to test these assumptions to ultimately create a rule by which all future subject lines are created, such as:

• Subject lines should be less than 35 characters.
• Subject Lines should include our company name.
• Subject Lines should contain the recipient’s first name.

Important Note: these are examples of best principles and should not be applied uniformly to your emails as a “best practice.” Again, best practice for Company A could be worst practice for Company B!

Change the conversation.

To successfully optimize, your testing should not stop when the tactical campaign is over. Your testing should follow all the way through the demand funnel to Closed/Won (or lost, but we’ll assume the best here). As we’ve mentioned in previous editions of {Demand Gen Brief}, all of your programs should be specifically designed to create forward funnel movement, and should be built around a specific process. Optimizing only a part of the process will not provide the end-to-end improvement you want.

Notes:

Testing must be performed with an overall objective in mind.

Tactical testing is not generally applicable over all of your campaign tactics.

Build your optimization framework around principles that can be applied to multiple tactics.

Next week, we’ll look at misdirected testing and how you can avoid falling into that trap: Three Ways A-B Testing Will Improve Your Marketing. (Part 2) How to Avoid Misdirected Testing.