Marketing Automation and Lead Management Blog

The #1 Factor in Executing Effective Campaigns

It’s the data stupid! Segmentation of your database, and the quality of the data therein, is the most important factor in determining the outcome of marketing campaigns. I read two items this week that reminded me of this important concept. First I read an ancient article on the 50 year old practice of RFM segmentation. No, that is not “Read The…Manual”, it is Recency, Frequency, and Monetary segmentation, something the direct mail business has practiced successfully for 50 years. The parallels to our B2B marketing automation supported lead nurturing world are amazing. We tend to consider recency and frequency of prospect interaction in determining a lead score for instance, and use that lead score in segmentation (to which campaign should I add or delete them?).

The second document I read was Ian Michiel’s document on Lead Lifecycle Management published in July 2009. In it Ian explains Aberdeen’s findings that best in class companies who improve their lead management (and thereby get better business results) are also substantially better at segmenting and targeting and have formal lead nurturing programs.  The important thing to remember about the data in your segmented list is that it is the first in a chain of variables that affect your campaign performance, and being first it can have a huge ripple effect on all the other variables (“Does the flap of a butterfly’s wings in Brazil set off a tornado in Texas?”).

If you are serious about improving the effectiveness of your outbound lead nurturing campaigns you are best served by improving the variables starting at the left and working to the right! Attempting to dial in all 6 variables at the same time is not going to get you to the best campaign results fastest. But I digress!

What’s wrong with ‘spray and pray’ marketing campaigns?
Back in the old days, prior to email, direct mail was the primary medium for direct communications. And if you didn’t segment you could waste a ton of budget on printing and postage! These days the direct medium of choice is usually email which is practically free. So what’s wrong with spraying and praying? It doesn’t really cost us anything more once the campaign is set up, does it? It does!

• It can be very difficult to determine what messages are resonating and what offers are successful if you send them to broad audiences, mixing industry verticals, titles, geographies, etc. ie you limit your ability to measure effectiveness and improve results by spraying broadly.
• After you send 2 or 3 irrelevant messages to an individual you effectively inoculate them; your chances of getting through to them with the right message later on are diminished. Even if they don’t unsubscribe, chances are good that you will be diverted to their junk folder in the future. You only get one chance at a first impression…
• If you spray, then the chances are that your message and offer will be watered down to the most common denominator. You will likely be sending some “me, me, me, it’s all about me” style documents and offers.  Nurturing emails that work best are in fact the “you, you, you, it’s all about what you need” type, as mentioned in Brian Carroll’s good blog post recently. And you can really only make these offers effectively if you have segmented narrowly!

By not segmenting do I undermine my marketing metrics?
If you want to convince your boss that the offers and email copy you are creating are brilliant, and you are getting much better open rates and clicks than the industry average,  then by all means mix in current customers, competitors,  and employees with your new prospects on that product 101 emailing! All of these people are great for bumping up open rates!  Good luck improving that campaign.

Can poor data hygiene affect my marketing metrics?
Of course! Garbage in Garbage out (GIGO). What if 20% of your list are duplicates, 20% are unsubscribed but fortunately blocked by your email provider, 45% are public domains,  5% have typos in the domain name and so will bounce, 1% have parenthetical sales notes in the first name that you used to personalize the email, and 15% got the default signature and contact info in their email of some guy in service because he is erroneously  assigned as the lead owner. Good luck improving that campaign.

The most important contributor to effective campaigns is the data you begin with, so for heaven’s sake allow only clean data in,  keep it clean, and segment it well!

-Kevin

 

Marketing Accountability is NOT a new concept

I have seen several blog posts recently that practically suggest that Marketing Accountability is a new concept. It is not new. Marketers have measured, and were held accountable for their results for decades! Primarily B2C marketers. Marketing accountability may however be new for some B2B marketers. Why?

B2C companies have used radio, TV, print advertising, and in store promotions, for many years, and measure the costs, impact to consumer behavior, and the cash register. The investment and the reward metrics are well beyond what many B2B marketing firms can imagine. $500K for software databases and associated campaign management tools, millions for the actual media, and tens of millions in returns within weeks of the campaign launch. By golly these marketers are accountable, and they must be laughing at the B2B marketers who think they are inventing marketing accountability!

Why has it taken so long for B2B marketing metrics to achieve the same level of sophistication as B2C? I believe there were several significant hurdles to B@B marketing accountability that marketers are now surmounting with the help of marketing automation.

B2B has multiple people involved in a single sale

In B2C you segment, target your list of consumers, launch, and measure results all within weeks in most cases. In B2B there can be many people involved in a single purchase. There can be a committee of decision makers. Different people can be involved in the sales cycle at different times; did purchasing ever elbow their way into your negotiations at the last minute and delay the contract a month? So if you are to successfully deploy marketing metrics you have to be able to gauge the aggregated marketing influence on all the stakeholders as it relates to the single final outcome. This is not as easily done as one promotion to one individual to drive one result.

B2B has a longer sales cycle
Length of the sales cycle is probably the most significant difference between B2B and B2C marketing. In B2C typically the purchase price is less than $100, so a single promotion can alter their perception of the brand and motivate the potential buyer into action next time the need arises. In B2B the sales price is probably in the thousands and the product or service is more complex and requires a human to consummate the deal. The length of the sales cycle can vary from weeks to years for the same product. ie you can have a "long tail" with a significant number of deals taking more than twice as long as the average. So if you are to calculate the Marketing ROI for some campaigns, how long do you wait for the deals to come in? The average sales cycle period, or twice that period? That could be 2 years!

The common fruit fly is very popular with geneticists because it can go from egg to an adult ready to breed in less than 10 days. So they can do lots of tests in a single year. The same applies to B2C. With a short sales cycle, marketers can test a campaign, wait a few weeks for results, adjust, test again, adjust, and then roll it out to a much larger region. For B2B with the longer sale cycle this is often not possible. They get one shot, and the real results based on revenue won't be known for a year, or two. One common error you see in B2B is with some marketers getting impatient for results and switching tactics before the long term effect of a campaign can be measured.

Multiple interactions with multiple media
Another challenge with B2B marketing is that we tend to have many interactions with prospects before we get to a sale. There can be trade show interactions, web site visits, direct mail, email offers, webinars and so on. So the final revenue won has to be credited to multiple interactions, to multiple stakeholders, all using multiple media and varying offers. Phew.

B2C marketing metrics are better suited for statistical analysis
Another item that works for the benefit of B2Cs is having big numbers for statistical analysis. If we want to measure something with a 95% confidence level, +/- 5% on a population of 10000 or more, we would need 400 in our sample size. With B2C they can do tests on one or two metropolitan areas, with a few million consumers and get statistically valid results. For B2B, 400 closed deals could be 100% of our annual sales! So it is much harder to apply statistics to smaller sample sizes and draw believable conclusions.

B2B Marketing Metrics for Marketing Accountability
The B2C marketers amongst you are now saying, "stop whining and do something about it". Okay so what can we B2B marketers do to increase our marketing accountability.
Create reports that aggregate all marketing influence per opportunity from all prospects related to that account. Get around the long sales cycle issue by measuring marketing influence on the shorter time period steps that make up the sales cycle.

• Measure the aggregated marketing influence on every closed won opportunity
• Measure the marketing influence on every opportunity in the funnel
• Measure the Lead conversion rate at every step (from Open, to MQL, from MQL to SAL, from SAL to SQL) based on marketing influence and lead source
• Measure the performance of each offer as it relates to opportunities.
• Measure the duration time of leads in each state (measures nurturing effectiveness)

B2B marketers are now getting sofware and database tools in the form of Marketing Automation that can measure their influence on the sales funnel and help drive marketing accountability. B2B are ready for a transition to data driven marketing. And the good news is that instead of costing $500K like the B2C software products, they are less than 10% of that number! So there is no excuse anymore!  Direct Sales has traditionally been the most accountable organization in the company with up to a third of its members turned over every year for not meeting plan. B2B marketing may have been the least accountable organization, but no more. The sales and marketing divide can be bridged with shared accountability for results.Don't expect what you don't inspect.

For those of you attending the CRM Evolution conference next week be sure to check out "B2C lessons for B2B Marketing" by Patric Timmermans.

-Kevin

Sirius Decisions Lead Waterfall – Lead Conversion Rates

Our Customer Service folks are working with a large client to implement a Sirius Decisions style dashboard for their leads. It shows the totals for new inquiries, marketing qualified leads (MQL), sales accepted leads, and sales qualified leads in any given time period. One of the trickier parts though is in documenting the conversion rate between these lead states.  If you thought the answer was just to divide the converted leads by the new leads in the period, you might want to think again. It will be in your favor to decide on the best method to calculate these conversion numbers before you present the lead waterfall chart. Knowing the conversion rates gives you a strong idea on how many leads you have to generate to fill the sales funnel.

Calculating the lead conversion rate

Let’s go through the process for just a single lead status transition – we want to calculate the conversion rate for leads with a lead status of “Inquiry” to leads with a lead status of “Marketing Qualified Lead”, or MQL, in a given time period, let’s say first quarter – Q1. This should be a nice measure of what percentage of raw leads Marketing is able to qualify and hand off to Sales! Typically the answer is 10% - 20% for B2B.

 Jan 1, there are 1000 leads sitting in the CRM database with a lead status (state) of “Inquiry”. By Mar 31, 300 new ones have been added to the database, and from the combined total of 1300, only 50 converted to “Marketing Qualified Lead”. i.e. their lead status value was changed from Inquiry to MQL!  Of the 50 that converted to MQLs in Q1, 25 of them were from new inquiries created in Q1 and 25 were from the 1000 fossils that were sitting around when we entered the quarter on Jan 1.

 So which of the following is the most useful or accurate conversion rate:

1. 50/1300 –  3.8%
2. 50/300 –  16.6%
3. 50/1000 –  5.0%
4. 25/300 –    8.3%
5. 50/(all the Inquiries created in the last n days)

50/1300 – 3.8% Inquiry to MQL Conversion Rate
This may actually be the most “accurate” answer, but it is certainly deceptive, and won’t make you a hero in marketing. The problem is this. If a lot of leads come in, create one response, and never engage with you again, they may remain in the “Inquiry” state for years. They never engage enough to become MQLs. Since the “1300” number contains the 300 new AND the 1000 fossils that were lying around when we entered the quarter, the fossil number could continue to grow and grow. Ie your conversion number would shrink every quarter even if you were converting new leads at the same rate!  So the 50/1300 without some form of expiration date for the fossils is a bad idea. More on the expiration later!

 50/300 –16.6% Inquiry to MQL Conversion Rate
‘Number out’, in the period divided by ‘number in’, in the period. It feels like the right thing to do but… In reality only 25, not 50, of the 300 new inquiries converted so it is deceptive, and if you use this method, and next quarter you do a fantastic job creating leads and add 600 new inquiries, and the same percentage of the new ones convert (50) and you get another 25 from the fossils, the conversion rate is 75/600  - 12.5% that’s a lower percentage than 50/300….but you actually did better because you generated more new leads!  Definitely don’t want to use this one!

 50/1000 – 5% Inquiry to MQL Conversion Rate
This is the total converts in the period divided by the starting number, and the conversion rate looks bad, and the more fossils that gather in your database, the worse this number starts to look. This number is the least likely to give people a gut feel for the waterfall. Don’t want this one!

 25/300 – 8.3% Inquiry to MQL Conversion Rate
This is the total of the new inquiries in the period that also converted in the same period, divided by total new inquiries in the period. This is very attractive in its simplicity but it is also dangerous. It ignores all of the conversions from the fossils. If the period of measurement is a year then the conversion number may be quite accurate, but if the period is a week, it could be wildly inaccurate. If the period is a quarter, and most inquiries convert to MQLs within 10 days it could be quite accurate, but if the time to conversion for new inquiries typically averages closer to 60 days this could be quite inaccurate. In our example, only half of the MQL leads in Q1 are converted from new Inquiries in the period so this means of calculating the conversion rate is only looking at half of the conversion data. The other problem with this number is that it can be quite volatile. If you do a big lead generation push in the last week of the period, and you don’t have a chance to convert many of those leads to MQLs, the conversion rate could look bad that quarter!

50/(all the Inquiries created in the last n days)
I like the idea of doing something like 50/total number of leads that had a status of Inquiry in Q1, and are younger than twice the average amount of time it takes for an inquiry to convert to an MQL. Let’s say that in our example above the average lead, if it is ever going to convert to an MQL, does so in 75 days. Chances are good then that after 150 days if an Inquiry hasn’t converted it can be put out to pasture. So we could consider for conversion purposes only those leads younger than 2x the average time to convert, and look at the conversion rate of this young bunch. We ignore the fossils.

So for our example above we would go back 150 days (2x75) from March 31, count all inquiries created since then that still had lead status=inquiry in the period Jan1-March 31, and use that as the divisor. If we created 400 new inquiries in Q4, but 25 of them converted in Q4 leaving 375, we would have a divisor of 300+375= 675.   The Q1 conversion rate is 50/675 = 7.4%.  So we are excluding all the truly old fossils from the 1300 number (total leads with lead status =”Inquiry” in the database in Q1), and looking at the younger pool of Inquiries that are most likely to convert. You will notice that this number is closer to the conversion rate for just the new inquiries (25/300=8.3%), but will be less likely to have the same volatility, and is more accurate. On occasion some of the old fossils (older than 2x the average time to convert) will convert so your "real" conversion rate is slightly higher than this. But let’s save that discussion for another long tail (sic).

Once you decide to pick a way of calculating conversion rates, stick with it, because the trend will become just as important as the raw number!

-Kevin

How and when to bypass lead nurturing

Are there times when Marketing should bypass nurturing and send a lead straight to Sales with "hot" status? Absolutely.

We have a Lead Nurturing webinar at 10am PDT next Wednesday and Thursday with NetProspex (ok that was shameless self-promotion), and it got me thinking about when NOT to nurture.(webcast of lead nurturing webinar is saved here).

FastTrack Existing Customer Leads instead of sending to a lead nurturing track!
Let's say you have a $200K/year existing account and its CEO suddenly decides to pop onto your website for the first time and download a piece of premium content requiring registration. Do you:

1. Ask her 20 questions including purchase timeframe?
2. Put her in a 9 month long drip campaign that pours out dreary whitepapers monthly?
3. Recognize that she is a customer based on her email domain?

The answer should be #3 of course. What you want to do is have the domain of every customer in a look-up list so you can compare all new leads to it, and then give them a boost in their lead score based their existing customer status. If a new lead shows up from an existing customer, the score should shoot to super hot (A+) and the lead should be sent to the Sales Rep immediately. Don't add them automatically to a drip campaign. Let the sales person decide when they review the lead if they are going to allow that person into a drip campaign, and which one.

FastTrack Strategic Account Leads After Lead Generation
The story is much the same for leads from target accounts. Just upload 500 of your favorite email domains, from strategic accounts or target accounts, and boost their score appropriately when they show up at your door. You might even consider making a unique score just for target accounts, and changing the subject line in the task (activity) you set for the sales rep to reflect that this is a new lead from a strategic account!

FastTrack Existing Account Leads
You may go one step further and decide that even if an account is not yet a customer, you don't want new leads from that account languishing in marketing land. You want Sales to be aware that another person in that account has just been added to the automated marketing system. Their score might be really low under normal circumstances, but because the account they are with is "highly qualified" you give their score a boost and deliver the lead to the Sales Force without delay.

SlowTrack Competitors, Analysts, and Vendors for more effective campaigns
Now that you have started to recognize visitors when they enter your marketing automation system based on their domain, you may as well have a SlowTrack. Recognize competitors, analysts, and vendors, and give them the lowest score, do not send them to sales, do add them to any lead nurturing programs, do not collect $200. If you want to have more effective campaigns, think about whom you exclude as much as you think about whom you include!

All of this is easily set up in Market2Lead with the derived attributes capability in the response funnel! Adding a "FastTrack" to your existing lead management process is important if you want to improve the quality and timing of leads sent to your Sales Force. Nurturing isn't for everyone!

Happy nurturing,
Kevin