Sales Thinks Your Leads Stink (Part 2): We need MORE LEADS. And yes, you can fix that!

Have you ever heard the phrase; “You made your own bed, now you have to lie in it?” This is the perfect example. As Marketing seeks to become smarter and evaluate leads quantitatively, the initial impact to the lead pipeline is going to be a sudden drop in volume. This will happen virtually every time. And the inevitable reaction from sales is a predictable as the sunrise: “We need more leads!” Let’s examine why giving in to this lie is a terrible idea.

Remember how we got here?
Let’s first recount how we got here. We came to an agreement between Marketing and Sales on what constituted a “sales-ready lead.” Those attributes were quantitative and measurable. Marketing created a Lead scoring system to evaluate every contact on the basis of those agreed-upon criteria. What is being passed to Sales fits those criteria. They have a name and are no longer generic Leads but MQLs or AQLs. Remember?

This is where the rubber meets the road, and demonstrates the importance of previous steps of gaining Sales agreement on the criteria for determining the meaning of “sales-ready.” This is also where Sales either becomes Marketing’s greatest ally or greatest enemy. And it’s your choice. But, before we get to your decision, let’s look at the math. Yes, math.

Look at the math. Because math is indisputable.
Let’s start with the demand before you, “We need more Leads.” And, for the sake of clarity, let’s call them by their proper name, Marketing Qualified Leads, or MQLs. The total number of MQLs is a function of two factors:

1.     Number of Contacts in your Marketing database.

2.     Conversion rates between funnel stages.

3.     Velocity of those Contacts from Prospect (or your top-of-funnel designation) to MQL.

How many Contacts do you need?

The number of Contacts affects your MQL output as a simple multiplier. For example, if your ratio of MQL to Prospect is 0.1 (10%), then you simply determine the number of MQLs you require by dividing that number by your ratio. In this case, if you need 1,000 MQLs, your simple ration equation is 1,000/0.1=10,000 Contacts in your database

Calculate your Conversion Rates.

Conversion rates are much more complicated to change, but should always be top-of-mind for Demand Center managers. Small changes to conversion rates have a big impact on your ratios and, by extension the required size of your Marketing database. The 10% MQL-to-Prospect ratio above is likely a combination of conversion rates between multiple steps, something like Prospect à Inquiry à MQL. If Prospect à Inquiry conversion rate is 50% and Inquiry à MQL conversion rate is 20%, you net out at an overall conversion rate of 0.5 * .0.2 = 0.1, or 10%. By improving the conversion rate between Prospect à Inquiry by 20%, we move that ratio to 0.6 or 60%. And, let’s say we move the Inquiry à MQL rate by 25%, we move that ratio to .25 or 25%. Now let’s look at the math: 0.6 * 0.25 = .15, or 15%. We actually moved the total ratio by 50%! Our calculation now looks like this: 1,000/0.15=6,667 Contacts in your database.

Velocity has impact.

Finally, the velocity calculation can increase your throughput to MQL. However, this calculation is difficult to measure and has the least impact on your ratios. Regardless, you should know it and be able to calculate it for your MAP platform. Velocity is simply time in stage. Velocity impact is time-in-stage*volume-in-stage. By reducing time-in-stage, we successfully improve our pass-though volume by the same percentage. For example, if your average time-in-stage for Inquiry is 20 days, this means you have Inquiries stacking up behind a 20-day “dam.” This analogy is a great way to visualize the velocity effect. If you can lower the time-in-stage by 25% to 15 days, you are allowing more volume through your dam by lowering its threshold. Imagine lowering a dam on a diver from 20 feet to 25 feet – what would happen? Initially, a flood of backed-up Leads would flow through. Remember, you will need to maintain the volume of incoming Lead flow to maintain this volume, once the threshold is lowered!

Brass tacks.

We now know what needs to change. The “brass tacks” question is how do we effect those changes. We need to ask these three questions:

1.     How many Contacts do we need at top of funnel to meet the required number of MQLs?

2.     What can we do to affect out conversion rates at each stage?

3.     What can we do to affect the time-in-stage to increase velocity?

The WRONG Response!

In many cases, the immediate response is to take the easy road to answer question 2. The easy road is to artificially lower the dam by reducing or eliminating the agreed-upon criteria for a “sales ready” Lead. (Bypassing Lead Scoring.) This leads directly to Cause A, and negates one of the key benefits of a Marketing Automation platform. It is quick, easy and completely wrong.

Change the conversation.

Let’s go back to the original demand, “We need more leads.” The conversation usually goes something like this:

Sales: What happened to all our Leads? We’re dying over here.

Marketing: Lead Scoring has reduced the quantity, but improved the quality of the MQLs.

Sales: What? I don’t care. I need more leads NOW!

Marketing: But we agreed on the criteria for MQLs, and we are sending exactly what you require.

Sales: I don’t care! I have 200 reps sitting around not making phone calls because the pipeline is dry! Do what you have to do to get me more leads today!

Marketing: That’s not so easy, since we set up the system to do what you requested.

Sales: I’m calling the SVP. This is BS. We need people to call. The Sky is falling and the world is coming to an end by noon.

Marketing: Ok, OK, I’ll turn off Lead Scoring!

And, you just wasted hundreds of thousands of dollars on Marketing Automation.

Instead, let’s have this conversation. We’ve established and agreed upon the definition of a “sales ready” Lead. We now have the calculations to demonstrate exactly what we need to generate the required number of MQLs. Based on this equation we can know ahead of time what it’s going to take to generate the required number of MQLs. Here are the two options:

1.     Marketing is provided the necessary funding to perform the necessary actions to meet the required number of MQLs, or;

2.     Sales can reduce its staff of sales reps to meet the number of MQLs that will flow through the system at current capacity.

How many times is option number two even contemplated? Is that just because Sales screams louder? Data will answer the screaming and help prevent Marketing from falling for the “We need more leads” trick at the expense of maintaining the quality of those leads.

Notes:

You must agree with sales on the definition of a “sales-ready” lead.

There are only three components of Lead volume Marketing can control.

Learn to calculate each of these components and let the math do your talking for you.

We looked at three “brass tacks” questions earlier, and you probably thought to yourself, “Great, but how?” And that’s an excellent question. Next week, we’ll dig into the “how” for both increasing conversion rates and stage velocity. When the boss asks you how to fix it, you need to be ready with the answers!

Sales Thinks Your Leads Stink (Part 1) Because they Really do? And yes, you can fix that!

In the ongoing battle between Sales and Marketing, Leads are often the major casualties. Marketing claims Sales doesn’t follow up on its Leads and Sales claims Marketing only sends over garbage not worth any follow up.

Who’s right?

Over the next few weeks, we’re going to dig into some statistics provided by Sirius Decisions and ask the simple question, “Why?” Here is the data:

20% of Leads are followed up by Sales

80% of Leads are never followed up by Sales

Conversely,

20% of those same Leads never purchase anything

80% of those same leads buy within 24 months (usually from somebody else) – if they are nurtured.

That’s a big IF!
The finger pointing begins and our ongoing battle rages. Is Sales correct? Let’s look at the possibility Sales is correct, and assume for a moment our “leads” are really not sales-ready. Identifying the problem is the first step to fixing it. There’s a straightforward fix, and you can implement it in your Demand Center in a matter of weeks.

Step 1: Get on the same page
You absolutely must work with Sales to determine what will be considered a sales-ready Lead. You cannot do this on your own because, in order for this process to work, Sales must agree on the definition. Marketing cannot define it for Sales, so collaboration is essential. However, that agreement must be stated in objective, quantifiable terms, not just the subjective “sniff test” (which actually doesn’t stand up to its own sniff test). What should those objective characteristics look like, given your sales organization is unique?

These objective characteristics should be broken into two categories: Profile and Behavior. For B2B marketers, Profile is the combination of demographic and firmagraphic characteristics of the ideal prospect, such as company size, title and department. For B2C, Profile will consist entirely of the demographics of the individual. Behavior is the digital body language expressed in online buying behavior. Has the prospect visited certain web pages, downloaded something or engaged in click-to-chat?

Once Sales and Marketing have agreed to the Profile and Behaviors that comprise an ideal Lead, you can move on to Step 2.

Step 2: Put a ruler on your Lead

Simply stated, how will you measure your objective criteria? Again, Sirius Decisions has created a model you can easily adapt to your criteria. Its co-dynamic model assigns values to both Profile and Behavior characteristics to create a score you can use to evaluate the sales readiness of a Lead.

I also recommend adopting the Sirius Decisions Waterfall terminology for describing “Leads.” If everything is a Lead, then nothing is a Lead. By specifically describing a sales-ready Lead by a different name that every other “Lead,” you provide clarity in your communications to the Sales team. Once you’ve defined your measurement system and labeled your sales-ready Leads accordingly, you can move to Step 3.

Step 3: Act on this information

Some data points are actionable and others are not. For example, there isn’t a lot you can do to get your prospect promoted from Manager to Vice President. However, you can create content designed specifically for your Manager to pass on to his superiors, thereby creating the potential for additional Contacts entering your system. This is called an Audience Acquisition Nurture. There’s that word: Nurture! Well-designed Nurture programs have very specific goals, and the tactics and content should be designed to meet those goals.

Nurtures are NOT about sending repetitive sales-oriented content out to large, untargeted groups of prospects. That strategy does not work, and I have a very specific name for them: opt-out campaigns. Because that’s what they do, get more people to unsubscribe from your communications than respond to them.  

These three steps will effectively eliminate the “Your Lead Stink!” argument from Sales. How can Salespeople complain about Leads sent to them exactly as they requested? This is where the objective criteria and measurement comes into play. If they ask for VP and above in IT who have downloaded trial software, and that’s what you send them, the question then becomes why did Sales agree to that definition of “sales-ready?”

Notes:

You must identify the problem before you can fix it.

You must agree with sales on the definition of a “sales-ready” lead.

Your definition must be in quantifiable, objective terms.

You need to act on the information you have.

So, let’s say your Marketing team has agreed to a sales-ready definition, and there is still a problem with passing Leads to Sales that they still don’t believe are good enough. You have fallen victim to Cause A, the Sales argument that they are not receiving enough Lead volume. Like any other problem, Cause A can be fixed. Next week, I’ll tell you how.

Top Ten Demand Generation FAILS (Part 10) The Missing Link!

Last week we looked into the secrets to reporting, and we’ve got it properly lined up before we launch our campaign. We’re going to report on MQLs generated by territory for our new Wombat preventer SaaS software. We’ll need to consider both outbound sources and inbound sources from media, such as Wombat Weekly and The Wombat Report. Just one problem: we don’t have Australian contacts in our database, not to mention critical opt-in data. And the only market for Wombat Preventers in is Australia.

Incomplete and incorrect data account for many, if not most, of the problems marketers have automating campaigns.  We’ve mentioned before that data is one of the critical interdependencies required in the demand gen process. Data is the fuel that helps us make critical decisions. Bad data equals bad decisions.

Over the years, I’ve seen a lot of databases and, as you can guess, in 100% of the cases they contained significant levels of incomplete and incorrect data. The best I’ve ever seen contained 45% incorrect or incomplete records. You don’t want to hear the worst. Having said that, also in 100% of the cases, we were able to identify the problems and make significant improvements to the data. How? Let’s look at some things you can do to improve your data quality starting today.

Identify your requirements.
Where have we heard that before? Right, everywhere! Without an objective, there isn’t any way to know whether or not your data is right, wrong, or incomplete. How do you intend to use your marketing data? Make a list in the form of questions you need to pose to your database, and include all the decisions you will need to make. This list will include questions like:

What is the Contact’s vertical market?

Where is the Contact located?

Is the Contact a current customer?

How many employees in the Contact’s company?

These segmentation questions help you form the basis to understand what information needs to be accurately recorded in a Contact’s record in order to extract these answers.

What decision will I make based on this information?
This is a great way to determine how you need to record field-level information, often referred to as field standardization. There is no universal answer to this question, because every organization uses unique rules in their business. You will need to determine this in relation to every question posed in the requirements section above. Let’s look at a pretty universal requirement, “Where is the Contact located?”

This is almost always (if not, you need to consider why not) composed of several fields used in conjunction with each other, such as Address, City, State and Zip. Some businesses also use telephone area code to determine physical location. Your database may use different field names, but they are going to be similar. What decision will you make based on this information?

Are you determining sales territories for lead routing? Do you execute location-based marketing programs? Do you sell different products or services in different geographies? Are you a global marketing organization and need to consider email compliance in various countries? Does your marketing message need to be localized to consider different cultural implications?

The answers to these questions can range from very simple to extremely complex, depending on how the decisions intersect. In many cases, you will be making multiple decisions based on location and, if so, do these decisions have conflicting data requirements? For instance, are your sales territories (lead routing) divided by area codes while your market localization is divided by metropolitan area?

Where are the holes?

Now that we know what decisions we need to make based on our data, we can begin to identify the holes. Those holes always manifest in on of two ways: incorrect data or incomplete data. In our example above, we need to understand major metropolitan areas so we can create location-based marketing messages. Perhaps we have affiliate marketing programs with the local sports teams. If so, how does our system know that St. Charles is a suburb of St. Louis? Do we need a zip code lookup table, or do we need a field with a specific MMA value to determine our target market? In this case, we need to add a missing data element to make up for the incomplete data preventing us from making a decision.

Our use case also requires us to route leads by area code, because that’s the way our sales territories are divided. Since we know from previous {Demand Gen Brief} posts our data degrades at about 25% per year, our phone numbers can go bad at the same rate. People move, change jobs and retire all the time, so we need to keep our data fresh, so your sales reps don’t follow up on a hot lead only to find out John doesn’t work in that department any more. (Cue the snotty email from your sales rep.)

Data governance and regular hygiene are the answer here. Whether it is in the form of data plugins that constantly update your database, or in the form of quarterly refresh imports, your data needs a regular cleansing so it doesn’t start smelling like last week’s garbage.

To take this particular use case a step further, how will you act on the area code data? Does your MAP platform have the ability to use part of a field to perform programmatic decision steps? Can it use CONTAINS or STARTS WITH as operators in decision blocks? If not, you may need to consider how to extract area code into a separate field that is actionable in your system!

Data is the missing link most often overlooked when building a demand gen strategy.  Don’t make the mistake of not designing your database to very specifically answer the critical questions you outlined above. If not, you may be relegated to considering specious Bigfoot sightings to find your Demand Gen missing link!

Notes:

You can’t properly design and build your database without clear requirements.

Be specific when asking yourself, “What decisions will I make based on this data?”

Find the two holes in your data: incomplete and incorrect data.

Don’t let this happen to you! We’ve now reviewed the Top Ten Demand Generation FAILS, and I hope I’ve presented actionable solutions to those fails. Next week, we’re going to switch gears and look at why Sales thinks your “qualified Leads” stink. Do they? Really?

Top Ten Demand Generation FAILS (Part 9) Ex Post Facto Reporting!

Here’s the situation. Your Demand Gen team has been asked to create an email campaign for a new product announcement, Product X. This campaign includes several emails, product data sheets and a complete microsite with multiple links to assets. Being the great demand gen professional you are, you provide a checklist of metrics for reporting and ask your product manager stakeholder if these campaign reports are required and if any other reports might be needed.

Clicks from emails to microsite? Check.

Clicks from microsite to form? Check.

Form completion and abandonment? Check.

Campaign-generated MQLs? Check.

Anything else? No, that will do it.

Geography, named account clicks, other segmentation reports? No, what you said is perfect.

So you create, receive approval, launch and complete your campaign exactly as requested. Two months after the campaign concludes, the very same product manger fires off an excited email proclaiming the VP of Sales needs a report on the number of Product X named account respondents from Vermont for a meeting in 30 minutes. After wasting 10 minutes digging the document out of the archives, you send back the written campaign brief indicating the report requirements, which specifically excluded both geography and named accounts.

But the VP of SALES needs it NOW!

I don’t’ care if the Masters of the Universe and Elvis Presley want it, the data doesn’t exist and that report can’t be generated.

Well, you already know the rest of the story. The product manager fires off angry emails to the VP of Sales, CC-ing the VP of Marketing, the COO and Oprah, for good measure, indicating what a buffoon you are and how you could not produce a “simple” report. This is a classic example of Demand Gen Fail number 9: The Ex Post Facto Report (reporting retroactively).

You will be vindicated in the end, but damage has been done and a massive amount of your valuable time has been wasted defending your perfectly executed campaign. How can you prevent these situations? Three steps will dramatically help.

Review the written process
In a previous edition of {Demand Gen Brief}, Top Ten Demand Generation FAILS (Part 4) Where is the Menu?, we talked about formal process. IN that edition, our “menu” was the analog to the various parts of our process, including the order in which those tasks should be completed. Reporting is a key consideration for every campaign, and the metrics of success must be captured if success is to be measured. As a part of the campaign brief (or whatever you call the campaign design document), the elements of campaign success should be clearly outlined. Having the key stakeholder answer these three questions can capture those:

1.     What will determine the success or failure of this campaign? This should be an open-ended question. The stakeholder needs to document, in his or her own words, what those elements are. It should be in the form of X units of Y by when.

2.     What are the subdivisions of those success metrics? These categories will be the ways you can subdivide the whole of Y in the success equation. For example, if Y is expressed as MQLs, are those MQLs of a specific size, location, vertical or product line? How many ways does this need to be sliced and diced so that all stakeholders are represented?

3.     Are these report formats sufficient? This is a yes or no question. You should present examples of the reports representing the success metrics, and make sure the stakeholder understands what reports will look like. Never ask an open-ended question around report format, because you won’t be able to produce the magic dashboard that transforms mashups into clickable charts that perform “deep dives” into the thought patterns motivating buyers in Croatia, sorted by three levels of stakeholders breakfast cereal preference. This yes or no also allows you to respond to such requests before the fact (pre factum), eliminating surprises.

Get a signature
Sounds simple, doesn’t it? You have reached an agreement to deliver a specific product at a specific time, just like any other contract. So, get a signature, indicating agreement between the two parties – in this case, the Demand Center and the requesting stakeholder – defining the terms of the agreement. Reporting is one of those terms. No, signature? No campaign. If this were a contract to sell your house, would you proceed without the buyer’s signature? A signature indicates a commitment to the terms of the campaign. Ambiguity hurts both parties, so eliminate it as much as possible.

Broadcast your methodology

Let everyone know how your Demand Center operates. You act as an internal agency, so run your operations in the same way. In the example above, the VP of Sales would have known that there was a previous commitment to deliver specific reporting, so the questions would have been directed at the Product Manager instead of you. (VP to Product Manger, “You asked for reporting by geography and named accounts, right?”) It becomes very clear very quickly where the broken link was.

Don’t let your lack of project management certification of experience inhibit you from instituting basic project management in your demand center organization. Even basic management will reduce inconsistency, improve timeliness and reduce errors. Any of these improvements will likely reduce the #1 complaint!

Notes:

The right time to determine necessary campaign reporting before the campaign is designed.

Review the process with requesting stakeholders every time. It will get shorter and easier as stakeholders get familiar with the process, but the review is necessary to proper understanding.

Treat the process like an external agreement – complete with all the details necessary to understand that a campaign – including reporting - has been completed according to the agreed-upon specifications.

We now understand what reports are going to be required before we’ve designed the campaign. Fantastic! We’re going to report on MQLs generated by territory for our new Wombat preventer SaaS software. We’ll need to consider both outbound sources and inbound sources from media, such as Wombat Weekly and The Wombat Report. Just one problem: We don’t have Australian contacts in our database, not to mention critical opt-in data. And there’s no market for Wombat preventers in North America. Missing data? This leads to Demand Gen FAIL number 10: The Missing Link!