I’ve come a long way this year - working hard at being a good father and developing a close bond with my son and I couldn’t be happier. I would encourage you to take some time to reflect on changes within your own life and the impact they’ve had on you whether it was a new job, a new home or a new perspective you’ve taken in your life.
I’ve also just passed my five year anniversary at Eloqua where I’m a Regional Manager on the Customer Success Team. I’ve seen many changes both at Eloqua and in the marketing automation industry over this time. In this post, I’m going to focus on how the process of developing a lead scoring program has transformed over the years. But first, let's go back in time to a typical (yet abbreviated and simplified) conversation around lead scoring circa 2005:
B2B marketer: “The sales team thinks the leads we send them are garbage. For them to take marketing seriously, I need to deliver higher quality leads rather than just focusing on quantity. What should we do?”
Me: “Implementing an automated lead scoring process should help here but it will depend on the lead management definitions you currently have in place. How do you define what a qualified lead is? Is this something that both marketing and sales agree on?”
B2B marketer: “A qualified lead is someone that has a specific challenge that our product can solve, has the budget to pay for our product and has the authority to get the deal done”.
Me: “OK, assuming you have worked out the specifics and have buy-in from sales, what are the key online behaviours that would indicate that one lead should be rated higher than the other?
B2B marketer: “Well, if the lead has attended an event of ours, let’s rate that higher and if they’ve visited 20+ pages and opened 5 or emails, I would consider that someone our sales team should follow up with”.
Based on these discussions, the marketer would further define her/his requirements and then go and build out the lead scoring program. Hopefully the assumptions made were correct and more qualified leads would be passed to sales. These were also the days of the “big ‘ole forms” on your website where you asked for every piece of BANT question that sales wanted and assumed that the data provided by registrants was accurate. If you found you weren’t getting enough qualified leads, you adjusted your lead scoring program accordingly based on feedback from sales and by reviewing the data.
|The Hover Board|
The accuracy of data captured has decreased over time
Techniques such as progressive profiling where you build the visitor profile over time assists in developing more accurate data to score on. The progressive profiling technique should only ask the required information that a company needs for the specific buyer stage that the web visitor is in. If someone is signing up for a newsletter, only a few details such as a person’s email address and their preferences should be required. Additional information can be slowly obtained in a future campaign such as a multi-touch lead nurturing program. In addition, progressive profiling allows the marketer to record online behaviour that can feed into the scoring process.
Automate your data cleansing process
A solution to this problem is an automated process called the “The Contact Washing Machine”. The goal of this program is to review the data that is fed into it and normalize it. For example, if we take the job title example, a Contact Washing Machine would bucket titles into specific categories as defined by marketing. Database records are updated with this normalized title which can then be used for scoring and other segmentation purposes. A great example of a Contact Washing Machine is provided by Amit Varshneya who is the VP of marketing at Hexaware Technologies.
Scoring should reflect the buyers’ journey and your defined sales/marketing stages
By going through the process of mapping out the content that your buyers accessed at various stages in their evaluation process, it ensures that the actual score and associated ranking of leads is more accurate and provides a better indicator to sales on how to prioritize their follow ups. In fact, in a DemandGen Report survey called Transforming the BtoB Buying Process found that “more than 8 in 10 respondents said the buying process did not follow a traditional path where a budget was established”. Therefore the BANT criteria is not enough to accurately assess leads and may actually prevent sales ready leads from rising to the top.
As a best practice, I now recommend breaking out the explicit lead scoring criteria (job title, lead source, size of company) from the implicit criteria (activity) to provide a more accurate picture for the sales team that they can action on. Therefore, you may have a lead with a low explicit rank of a C (where A is the highest and D is the lowest) but has a high implicit score of 1 (with 1 the highest and 4 the lowest). This combined lead rank of C1 is a lead that sales should prioritize as the explicit information provided may be inaccurate but the implicit criteria or the Digital Body Language demonstrates that this person is definitely interested in your company.
In addition, best in class organizations have tied their sales/marketing funnel to their lead ranking definitions. Therefore, in order for a lead to be considered a marketing qualified lead (or MQL as defined by SiriusDecisions Demand Waterfall), it must attain a certain lead ranking such as A1 or C2. To the right is a good visualization of how an MQL may be defined when using Lead Scoring.
I’ve also included a great video that shows you how this is used in the lead management process:
Here are few examples that I recommend you review to get a better feel for this concept:
- Terracotta: Lead Scoring A Buyer’s Journey in Open Source. In this example, Terracotta mapped out the different types of behaviours that made up the different stages that a buyer progresses through. They then used this to build their lead scoring matrix and constantly tweak the lead scoring algorithm to get more accurate results.
- Taleo: Seeding and Cultivating the Taleo Revenue Engine with Lead Nurturing. The VP of Marketing Doug Sechrist stated “We built a matrix that looks at the buyer’s journey and our sales cycle, and based on that, we determined the right content for each touch point.” Besides lead nurturing, the buyer’s journey influenced its lead scoring rankings and determined the stage of the buyer. The case study goes on to outline how Taleo only sends A and B rated leads to inside sales as these are defined as MQLs (marketing qualified leads).
How marketing is now measured has made lead scoring more palatable
I don’t have to look any further for an example of this exact transformation than from within my own organization as described by our Senior VP of Worldwide Sales, Alex Shootman, in his post: At The Wheel of the Revenue Machine: But What if I Want to Follow Up on “D” Leads?. It took a shared goal of increasing revenue and a commitment from sales and marketing to work closer together to help make scoring more relevant in the lead management process. And guess what – if you’re reading about this, you can bet that your competitors either have lead scoring in place or are considering it. Don’t wait for them to beat you to the punch.
I’m sure others can add additional points on how lead scoring has progressed over time but this is one of the few chances I get to sleep and I need to take advantage of it while it lasts! Do let me know if you think I’m missing anything. On a final note as I wrap this up I would like to thank my wife, Allie, who has made being a father easy over this past year and has been such a wonderful mother to our son. I would also like to thank all of the Eloquans – past and present, partners, and customers that I’ve had the pleasure of working with over the past five years and plan to continue working with.
PS – For something fun, check out Juan Eloqua and the Grande Guide to Lead Scoring