Marketing Automation and Lead Management Blog

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

Definitions for marketing leads for use in lead generation

I just finished reading Brian Carroll’s erudite blog post on Five steps to help create your universal lead definition. In 10 years of working with firms on marketing automation and lead management there have been far too few that had this important definition agreed to by Marketing and Sales.

Marketing’s primary deliverable to Sales is the marketing qualified lead.  Not having a firm definition of this deliverable is unforgivable. How can marketing be held accountable if there is no definition for a good lead? Notwithstanding Brian’s advice on how to organize around arriving at a lead definition, here are a few items to consider in the lead definitions.

Marketing Lead Definitions

Most folks use the lead status field as a means to differentiate between leads of various qualities. Do not use this field as a call disposition field (‘left message’, ‘contact successful’ etc). Limit the number of Lead Status values to 10 or 12 at the most. Remember at some point you will be reporting on how many leads are in which state, and how long did they remain there. Consider this the marketing funnel report and you want to be able to demonstrate a steady flow through the various lead states!

• Raw – person identified as worth engaging, no relationship yet, probably a list import
• Open or Inquiry or New or Suspect– person has at least one incoming response, or otherwise expressed interest somehow
• Lead Qualification – person sent to lead qualification (telemarketing) for qualification
• Marketing Qualified Lead (MQL) – person that marketing feels is ready for Sales' attention
• Sales Accepted Lead (SAL) - a person that may represent a new opportunity. Once a lead is known to be associated with an existing account or a revenue opportunity, it becomes a sales qualified lead and is converted into a contact.
• Sales Qualified Lead (SQL) – Use this as the final resting state of a lead that is converted into a contact by the Sales person in your Customer Relationship Management system!
• Disqualified – Someone who will never rise to the level of qualified and is not worth any future attention from marketing and sales.
• Junk – Bad data, "asdf@abc.com" and the like. It is useful to flag this separately from Disqualified because (a) you can later on determine which lead source is producing the most junk, and (b) at some point you may opt to delete all junk from your database but you will want to retain the Disqualified folks. "Disqualified "is still good information, and you never want to go through the process of qualifying them again!
• Re-Market – person sent back to marketing by sales because it was not ready to become a Sales Qualified Lead.

So in the meetings between Marketing and Sales you need to arrive at definitions for each of these lead status values. The most contentious one is the Marketing Qualified Lead. What information does Marketing have to know about a lead before handing it off to Sales.  I won’t repeat my blog post on BANT versus the SCOTSMAN but it is worth a read if you are interested in this topic.

Very few leads should remain in the Sales Accepted Lead state. When a lead is handed off to Sales they will have a limited period of time to either accept it (change it to a Sales Accepted Lead), Disqualify it, or return it to Marketing for further lead nurturing (change it to Re-Market).

There are some further twists on these definitions based on dealing with ISRs,  channel partners, and methods to fast track certain leads through the process. We will save that discussion for a future time. As always, comments welcome!

-Kevin

Website tracking from Web Analytics vendors vs. Marketing Automation vendors

I get asked by many Prospects during the sales process about the difference between web tracking functionality offered by web analytics vendors like Google Analytics and Marketing Automation solutions like Market2Lead. There is a definitely an overlap between the two types of solutions, but at the same time there is a significant difference too. Let me elaborate.

Traditional Web Analytics tools like Google, Omniture or Coremetrics do a great job in tracking and reporting on overall traffic trends on the corporate website.

• You get to understand where traffic is coming from – Direct Traffic, Referring Sites or Search Engines
• You can track popularity of content on your site – page views per page, bounce rates
• Monitor overall metrics - Visits, Pages/Visit, Bounce Rate, Avg. time on site

Web Analytics vendors do a great job in helping you understand how your corporate website is contributing towards overall Marketing goals like awareness, brand building and demand generation.

You can get some of these metrics from the current generation Marketing Automation solutions that do offer website tracking as a feature (including Market2Lead). But this should not be the key criteria for you to evaluate MA solutions for this feature.

There are 2 key aspects that are unique to MA solutions. 

1.    Web tracking by user/company profile: Marketing Automation solutions give you the ability to track usage patterns by profile of your Contacts or the companies they work for. Marketing Automation systems are the record keeper of your house database and have rich profile information like Demographic, Firmographic, Needs Insights etc. Now, imagine the power you have at your disposal if you can combine a person’s information with his web activity information. You can conduct all sorts of interesting analysis like:

• What % of my traffic is executives/VPs/Directors/Managers/IT
• What % of my offers are being picked up by people with different roles and managing different functions within their companies
• What % of my content is appealing to SMB companies/Midsize companies/large enterprises
• Is my contact’s online behavior validating the interest he/she expressed in filling out a form

2.    Notifications to sales reps: You can now alert your sales staff based on key web activities that are recorded within your MA solution. Sales reps are always looking for the right reason to pick up the phone and call their Leads or Opportunities. Some of the scenarios where MA solutions can help are:

• A key opportunity that went dark during the negotiation phase is reviewing case studies on the website. Such information gives reps the assurance that the Opportunity is still active and is evaluating risk by looking for relevant case studies

• A Lead that stopped responding to phone calls was spotted on the website. This is a great opportunity for the rep to call the Lead and hope to connect with him/her while he/she is still at his/her desk

• Give reps a better qualified Lead that has not just filled a form but has demonstrated interest by invested an appropriate amount of time reading relevant content

• Assist Leads who are trying to understand your value proposition by sending them follow up offers based on what they are reading on your website

In my opinion, web tracking functionality from Marketing Automation solution is complimentary to web tracking from the standard Web analytics tools.

-Sundeep

The SCOTSMAN vs. BANT for Effective Lead Management

In his recent Blog post on Sales and Marketing Alignment Brian Carroll alluded to sales and marketing collaborating on the definition of a "Sales Ready Lead". This is a really important topic as it is the basis of good lead management. I used to work for a Scotsman named John McAdam (he is now CEO of F5 in Seattle), and perhaps not coincidentally Marketing and Sales at the firm had an agreement called the SCOTSMAN. It is a mnemonic, along the lines of BANT but better. I believe every company needs to come up with their own equivalent of the SCOTSMAN as the basis for agreement between marketing and sales.

We used the Scotsman as a deal qualification sheet. The sales person wasn't going to get help from executives and marketing if they didn't have their Scotsman filled out! And you thought I was going to refer to a document dictating what info marketing had to provide to Sales on a qualified lead? Well it turns out that the Scotsman has something to offer in that department too, so bear with me.

SCOTSMAN Mnemonic

• Solution = Does the firm have the right solution?

• Competition = Who is the competition and can we beat them in this situation?

• Originality = Does the firm have a unique solution and has the prospect bought into it?

• Timescale = What is the timing for the desired solution?

• Size = How large is the opportunity?  Is the desired solution list price of sufficient for our needs?

• Money = Does the client have the money in the budget?

• Authority = Is the sales person talking to the people who have decision/purchase authority

• Need = What does the prospect really need (business problem)

The problem with BANT

When you think about it, the BANT criteria are all in the SCOTSMAN: Budget, Need, Authority and Timeframe but there are 4 additional items!   Solution, Competition, Originality, and Size.

How is marketing supposed to determine any of these things? Isn't that something better done by an ISR or "Outside" Sales Rep?  In my experience Marketing does a poor job of getting BANT. How many forms have you seen filled in with:

• Budget:         0 or other or don't know
• Authority:      Other
• Need:            Don't know
• Timeframe:    >1 year

Putting these questions in a form to propects who is just in the research phase at the time is ineffective. You may as well ask:"Would you like me to set a Sales Rep on your tail like a rottweiler looking for a steak?"

In this situation a large number of people will prevaricate (that sounds so much better than lie) to keep the sales reps at bay. As a marketer I would rather have no data than junk data. And to compound matters some marketers base lead scores off this BANT data. Caveat Venditor.  Putting poor quality data into your database by asking questions which encourage prospects to mislead you is a mistake.

Determining your own SCOTSMAN

As marketers we know that the sales folks want a lead with huge budget, senior role and a clearly defined urgent need for our unique product/service capabilities. Just because that is what they want doesn't make it a good basis for an agreement between Sales and Marketing. If we wait until we find those types of leads, they would be few and far between. Add to that the difficulty in getting honest answers to BANT like questions without using human interaction and you have a recipe for many disgruntled sales people. 

But, short of moving ISRs into marketing (which is the solution many people opt for) there are some ways that marketing can solicit data from prospects that is reasonable and stands a good chance of being accurate. Perhaps you can craft your own SCOTSMAN from these suggestions:

1. Use progressive profiling with dynamic forms - i.e ask one or two incremental questions each time the prospect engages with you, instead of the 40 question form on the first visit.
2. Ask business need related questions - in a pick list - which is most important to your firm, a,b,c, or d  (people are more likely to talk honestly about their firm then they are themselves)
3. Ask them their job function in a pick list but give them the option to say "I don't want to share at this time"
4. Inquire to the number of employees in the firm or division or department - this could be a better indicator of budget
5. Inquire about the likely frequency of usage of your product or service - this will give you an indicator of how much it is worth to them
6. Inquire about how many people work in an area where this product could be used - a roundabout way of getting to potential number of users
7. Inquire if they own or have owned or used other products or services like this - could mean a lot less education required for the sales person
8. Ask them their past experience if the answer to 7 was true - good, bad, indifferent - try to determine if they are a supporter of this class of product or service
9. Ask them if their research is in support of a company or department goal
10. Try to determine their role in the purchase by examining which documents, web pages and offers they pick up on - business vs technical, evaluator, influencer or interested party
11. Try and find out where they are at in the process in a nice way. Are they researching, just curious, looking at all the vendors products so they can educate themselves but it isn't even a project yet, narrowing down the list? Just don't ask the banal timeframe question so bluntly! They don't usually know.
12. Find out if they have a communications preference, are they more visual, or auditory, or do they learn from whitepapers. Do they want snapshots or books?
13. Do they want to feel inspired, protected, relieved, or fulfilled
14. Offer them help in their education/research work, would they like more materials, would they like a template RFP, do they need help selling their bosses on this idea, would they like an ROI model?

When you are done you may have your own mnemonic in marketing for the data needed to certify a lead as Marketing Qualified. Perhaps something like:

• Influence = Is this person in favor of a product or service like this, neutral, or oppose?
• Repeat buyer = Do they have prior experience with this product or service from competitors?
• Interaction = Paint a picture of their interaction level, how much have they educated themselves?
• Stage = Where are they at in their purchase process - what stage?
• Help = How can we help them through this phase - What have they asked us for?
• Money = Does the client have the money in the budget and how much?

• Authority = What level of authority does this person have?

• Need = What does the prospect really need (business problem), how are they going to use it?

Now what sort of mnemonic is that?

-Kevin

Naming Standards in Marketing Automation systems

I spent some time with a prospect yesterday and the topic of the importance of naming campaigns arose;   a rose by any other name would smell as sweet…unless of course it was the name of a campaign, program, list, form, template, folder, offer, import configuration, custom field, report, or dashboard in your new Marketing Automation system.  Didn’t realize that there was so much stuff to name? And if you let your marketing automation users make up any name they want to, and save everything  in the top level folders, you will have a mess on your hands in a year.

When you roll out your new marketing automation system, be sure to roll out a standards document on naming conventions. Here are some tips taken from our client services lead management and lead nurturing best practices documents at Market2lead.

• Unless otherwise specified name everything with the following format

  • <Object-Type>_<Date>_<Tactic  Code>_<Target_Segment>_<Description>
  • Webinar Example: WBN_2008_Nurture_NA_Healthcare_in-house
  • Newsletter Example: NLS_1108_Communications_NA_Federal
  • Use Acronyms where possible. They are hard to enforce initially but help in conserving UI real estate and standardization.
  • Years are shown as yyyy as in 2008
  • Month/year is shown as mmyy as in 0308
  • Quarters are shown QNYY as in Q308
  • Year, month, date as yyyymmdd as in 20080731
  • Not all items will have a region and market segment
  • Many Marketing Automation Systems will let you sort assets alphabetically so think about what that first word should be!
  • Capitalize the first letter of each unique word
  • Never use spaces – use underscore to separate items
  • Campaign type should match the CRM picklist for “lead source” exactly

• Try to name related items the same way. For instance a single marketing campaign may have multiple programs related to it that all should have similar names. A single webinar campaign might have:

1. A webinar registration form, email invitation, email reminder

2. Email sorry we missed you, email thank you for attending
3. A follow up survey, and several unique  invitation lists (production, seed, test)

• For campaigns organize folders by geography first. Within these folders organize content by year first and then by campaign type under that.

• For lists the top level folder should be the list type (production, seed, test, exclusion etc
  • The next level down is ideally the program or campaign type

• For forms make the top level folder the form type – inquiry, download, free trial, PPC, etc

• For custom fields added to contact or account records put a suffix on the name that tells you instantly if that field is one that syncs over to your CRM.
• Name reports in a way that captures some of the business rules inherent in creating the report
  • NA_Free_Trial-_Registration_Q308_Box_Cutter_Software 
• Create archive folders for assets and programs that are no longer active

If you create and enforce the standards, it will be a whole lot easier to find things a year from now!

-Kevin

What is a lead?

I enjoyed the conversation yesterday on Jep Castelein's blog on demand generation, wherein several of us debated the issues with labeling marketing automation systems as just "lead management" systems as some analysts are wont to do. It begs the question, what is a lead?

For many of us a lead is a person who may or may not represent an opportunity and who may or may not be deemed qualified during some future vetting process. As such this person is considered unique, and deduped in the marketing database, probably on the basis of their email address or some combo of last name,address etc.

On the other hand there are those firms out there who feel that a lead is an early glimmer of an opportunity for a specific product or service. As a result a single person, who may even be an existing customer, could be in your system multiple times as multiple leads for multiple products. Now I can see that this approach is a very sales driven approach. They want to believe that every human contact has immediate dollar signs behind it. Even the SFA systems, salesforce.com and MS CRM will permit multiple copies of the same person (based on email). There is a horrible downside (IMHO) to this approach - lots of dupes in the system - just whom are we marketing to? How do you track and ensure canspam compliance? Many of the marketing automation vendors won't allow you to have the same email in their system twice. Does anyone know of an upside to thinking of leads as imminent opportunities - it would be great to hear from you.
-Kevin

Economic Downturn - A chance to leapfrog your competition

It is interesting to listen to the economic pundits talk about whether we are already in a recession or whether we are heading towards one. While the popular definition is 2 continuous quarters of negative economic growth there are other interesting views about this definition. Here is an interesting blog post by two economic professors at UC San Diego and University of Wisconsin, Madison where the authors espouse that "recessions represent distinct and objectively identifiable episodes in which the usual dynamic factors that drive economic growth-- technological progress, population growth, and capital accumulation-- are replaced by a distinctly different dynamic in which lost income in some sectors feeds back into declines in output for others".

While economists fight out the technicalities of a recession what are B2B Marketers doing to brace for a period of sluggish growth (at best)? Here are a few areas that we at Market2Lead think Marketers should focus on in the near future so that they can emerge more effective and efficient when the economy turns around.

1. Consolidation & Automation - Eliminate rote work: Most businesses are extremely sensitive to cash investments vis-a-vis resource investments. Many potential clients that we talk to have a hodge-podge of systems/resources to manage their Marketing efforts. A typical mix includes email tools, data scrubbing tools, landing page tools or web masters, webinar registration tools among others. Some of these tools tie into the client's CRM system while others don't. A significant amount of operations resource time is spent in moving data between the tools, scrubbing data files and manually building reports by collating data from these tools. During recessionary times companies are forced to not just cut back budgets but are also forced to either cut back or extract more efficiencies from existing
resources. At the same time, work load typically goes up. The best way to work within these constraints and still maintain throughput is to consolidate systems. Now is the time to invest in a comprehensive Marketing Automation solution that will help automate/eliminate manual tasks. Another big benefit is Marketing departments will be able to spend time on strategic initiatives that can have a direct impact on top line revenue.

2. Lead Nurturing - Extract more from past investments: Sirius Decisions published a study that mentions 80% of Leads generated by B2B marketing are not followed up by sales. Also in times of slow economy growth most companies either delay buying decisions or are extremely picky in their buying decisions. This basically means that a slowdown in sales cycle time. The smart thing to do at this time is to shift focus from campaigns that drive new demand to campaigns that can nurture existing Leads. With cost effective tactics like emails, webinars, online syndication etc. lead nurturing campaigns are a lot more cost effective than demand generation campaigns. Marketing Automation solutions can help Marketers design and automate nurture campaigns that can extract more revenue from Leads that did not convert. A study published in Marketing Management V3 #2 suggests that 45% of Marketing Respondents buy in 12 months, not necessarily from companies that initially marketed to them. This is popularly called the "Marketing rule of 45" and has held the test of time for 3 decades. In this day and age, with a plethora of cost effective technologies and related processes, most companies barely manage to get a 5% yield from their campaigns. Now is the time to shift focus from Demand Generation to Lead Nurturing and extract more value from existing spend.

3. Funnel Optimization - Plug leaks: Marketing organizations need to scrutinize every stage of the integrated marketing and sales funnel and look for opportunities to increase throughput. Now is the time to look at conversion rates, qualification rates, sales follow-up rates and win/loss rates. Look at campaigns that demonstrate "Spray and Pray" symptoms. Figure out ways to optimize existing segmentation strategies and move towards an "Aim and Shoot" stage. In my observation, most organizations still lock and load a significant portion of their databases hoping for larger conversion numbers. Instead, focus on conversion ratios. You might get the same numbers by targeting a smaller audience segment. Next, talk to your sales organization and find out if there is a change in their capacity to handle Leads. Sales might be happier with fewer Leads if they are better qualified. You can positively impact sales morale and productivity. Recessions impact some industries more than the other. For example, in the current economic climate, it's a bad idea to go after the financial services market to meet revenue goals for the immediate future. Align your demand generation campaigns with industries that are relatively healthy when compared with the others. To facilitate this level of analysis your Marketing Automation system should give you visibility into the extended funnel and sales stages like lead promotion, opportunity management and forecasting.

4. Increase throughput - Implement best practices: This is a fantastic opportunity to take action on those creative ideas you had in mind to improve throughput from your campaigns. When the economy is roaring companies lay more emphasis on velocity to grow revenue aggressively. Inefficiencies are hidden or ignored when companies are in "order taking mode". When the economy slows down companies are forced to change behavior and become smarter. Budgets accommodate fewer campaigns and expect better results. Now is the time to wipe the dust off the best practice guides that you really wanted to implement but never got the time to. Try and micro-segment your campaigns and try different variations for emails, landing pages, microsites among others. MarketingSherpa is a great resource for case studies and best practices. Look for technologies that support A/B testing for emails, multi-variate testing for Landing pages, recommendation techniques for offers on microsites, progressive profiling techniques to improve form completion rates.

5. Measure, measure, measure - justify your spend: Marketer's are always under pressure to demonstrate return on their investments. The scrutiny is all the more pronounced during tough times. Every penny has to be justified and every campaign has to be measured. This job is relatively easy for demand generation campaigns since these campaigns are optimized for generating Leads. But demand generation campaigns always need support from awareness campaigns to build brand equity and buy mind share. As a Marketer, you know that you need to invest in PR and SEO to drive traffic to the website. How do you quantify the value from such investments to a CFO or a CEO who is trying to connect the dots between spend and revenue. The only way you can accomplish this is to be able to correlate data and trends from different initiatives and draw trends that can be quantified. This requires a robust Business Intelligence solution that will give you the flexibility to slice and dice data in different ways and look for interesting trends and patterns that can be used to justify spend. Imagine if you can view web traffic trends and marketing funnel trends side by side on the same dashboard and have the capability to analyze the impact of one on the other. It's a much easier argument to show your boss that by keeping the constraints constant on the demand generation side the quantifiable impact a dip in PR and SEO effort has on the funnel.

Recessions can be looked at with caution and skepticism or can be looked at as an opportunity to get lean, smart and more efficient. History tells us that smart companies emerge from down cycles much stronger and fitter and the weaker companies lose out.

Numeric Scoring Pros and Cons

I recently read a blog post by Laura Ramos from Forrester on the subject of Lead Scoring methodologies. In the article Laura outlines the key benefits of a "Numeric Scoring Model". I agree with Laura about the need for Marketers to remove the subjectivity about the quality of a Lead. I also agree with her about some of the best practices to help Marketing and Sales bring more clarity to this topic.

1. Sales & Marketing should have quarterly meetings to review the scoring model and tune it based on results from the previous quarter.

2. Implement a scoring scheme that is easy to understand and manage. One of the methods is to use Numeric scoring. In this method a Marketer would assign points to each key Contact attribute and a weight (both self reported data and behavioral data) and compute a weighted sum of the points to arrive at  the overall Score of a Contact. This method has its pros and cons. Laura already outlined the benefits of the Numeric model that I don't want to repeat here. Here are 2 challenges with this method that I have seen:

a. Chances of sending False Positives to Sales: With a scoring model that does not support a rules engine Marketers don't have the capability to check for data completeness and authenticity for key pieces of information without which a Lead is of little value to Sales. Let's look at a sample scoring scheme (to keep this example simple I have not added any weights to each attribute):

Here is a sample Lead based on this model:

In the above example  Bob gets a score of 95, which is a very high score, and needs immediate follow up from sales. But, from the data it is fairly obvious that the phone number is bogus and we have a hotmail address. Let's take an extreme case where  Bob's  information comes into the system without an email or a phone number. In this case the Lead will still have a score of 80 points (I subtracted 5 points for email and 10 points for phone number from the original score of 95 points). In both these cases the scoring model instantly loses credibility with the sales team and we all know what happens next. 

b. How is the Lead with a score of '68' different from a Lead with a score of '77'? We all know that sales people like to spend their time selling and not learning and understanding internal processes. The last thing we want to do with a sales guy is to open a spreadsheet with 100 items and a complex formula that spits out a number. The critical thing for Marketing is to prioritize the Leads for sales and set some thresholds for follow up. For example, Leads with 80 points and more need to be followed up within 4 hours; Leads with a score between 60 and 80 points need to be followed up within 8 hours and so on. A tiered scoring method (A, B, C, D) serves the same purpose.

In my view the scoring scheme (either points based or tiered) needs to be augmented with a robust data completeness and data validation process to ensure that sales gets to work on Leads that have a high chance of conversion.  One way to augment the scoring process is to add 2 pre-processing stages:

1. Data validity check: In this step we need to check for common junk data that people enter like 'test', 'aaa', 'asdf' etc. for Name, '111-1111', '1234567890' for phone numbers, 'a@a.com' for emails etc.

2. Data Suppression: Sometimes there are legitimate Leads that are generated from Marketing campaigns that are not necessarily sales Leads. We need to suppress such Leads. For example, emails have a '.edu' extension, the Lead belongs to a partner organization or an analyst firm etc.

I would love to hear your comments.