Feedback Enhanced Selling

Improving Sales Processes using Pre-Lead, Lead and Prospect feedback

As a career business development guy, I've always been intrigued by the potential of feedback enhanced selling.  And, in particular since I began representing QuestBack, a feedback management tool.  Yet even for me, until recently it seemed like collecting feedback from leads and prospects was just as easily done via direct e-mails or phone calls.  After all, what else are sales people supposed to do except directly communicate with leads, prospects and customers? 

When I look at sales jobs today, often the expectation is for sales people to contact 100 people per day by phone.  Now, no one expects anyone to have conversations with 100 people daily.  But these firms want their sales folks to dial 100 times a day in order to have maybe five meaningful conversations.  Every time I see this it bothers me.  It would appear that companies are willing to pay people to engage in behavior that results in essentially a 95% failure rate.  And, with buyers not answering their phones at all, will the number of calls be 200 a day next year or 500 five years from now?  I don't know.  But ten years ago expectations were for sales people to contact 50 leads per day.  So, the number is rising and unless a new process is found, its likely to continue to do so.

So the question is:  Is there a way to get from 5 conversations in a day to 6, 7 or 8?  I think possibly there is.  Using web or e-mail based surveys may offer a solution.  Some reasons leads don't engage with sales people are: Timing is wrong (no plans to buy for awhile), Solution "fit" is bad, or more preferable alternatives are available and "on the table".  Hence, no desire to talk to your sales people and no contact is made.  If done well lead feedback will help sales reps with timing their calls to contacts, with understanding the contacts needs and with avoiding contacting leads where no fit exists.  Result, less stressed sales reps, more targeted calling, more prospects in the funnel, happier and more qualified leads and prospects.  All good stuff.

Some thoughts on when to gather feedback from leads or prospects:

• During website visits.  Surveys should be offered to visitors regarding the information being presented.  Idea is to identify if the information provided is sufficient and helpful or if they want more or even a contact from you.
• After a lead enters ther sales funnel.  Survey should be done to ascertain sales cycle stage, needs analysis and timeline perception. Idea is to gauge interest level, understand budgets, determine competition and understand perception of your company's offering.
• After a sales person has made direct contact with a lead.  Idea is to determine if the lead learned what they needed from you to move forward.  And, did his perception of you improve or deteriorate?
• After an inside sales representative designates a lead as a prospect.  Idea is to validate the action and learn what the new prospect perceives about your offering that causes him to be interested in additional dialogue.
• After a "key account manager" has been in contact with a prospect.  Idea is to validate that the prospect sees the product fit and sales cycle in the same way your KAM has reported it.  Collecting feedback 30, 60 or 90 days after a relationship has been started should help with understanding the possibiltiies for a sale occurring.

Technology already exists to automate a great deal of this kind of effort. QuestBack has even built a series of templates to use for automating feedback collection from leads and prospects during the sales cycle.  An example of QuestBack's sales process feedback approach can be found here: 

http://www.questback.com/areas-of-use/private-sector/lead-generation/

A Repost of a Good Net Promoter discussion with pros and cons...

I've written in the past about the Net Promoter methodology for measuring customer satisfaction and loyalty.  If you've read any of my Blog posts, you'll realize that I'm a big fan of net promoter. And, I frequently recommend its use to my customers.

Earlier today I was browsing a LinkedIn group where I'm a member, when I came across this post (which was a repost) of an article originally published in MarketingWeek magazine. 

I thought the article gave a pretty good account of the Pros and Cons associated with Net Promoter and its use.  So thought I'd share it here.  Enjoy.  The url is:

http://www.linkedin.com/news?viewArticle=&articleID=374834583&gid=1772348&type=member&item=44620162&articleURL=http%3A%2F%2Fwww%2Emarketingweek%2Eco%2Euk%2Fanalysis%2Ffeatures%2Fhow-to-get-more-from-your-score%2F3023551%2Earticle&urlhash=iHgy&goback=%2Egmp_1772348%2Egde_1772348_member_44620162

Customer Surveys - Better results by Linking Responses with Business Data

In my last Blog post I talk about some things not to do in B2B customer surveys.  A big one for me is asking questions where the answer is already known to your company.  Business data is a huge area of customer questioning that fits the "Don't Ask" profile. Some examples of survey questions I've seen where business data is asked for:

- "How long have you been a customer?"
- "What region are you located in?"
- "Please select the [Company] products you have purchased or use?"
- "When did you make your last purchase from us?"

When asking this kind of question, the surveyor is taking a "short cut" by having the customer fill in or validate data that exists in the company's databases.   

The solution is to create linkage between customer surveys and business data.  By doing so, it is possible to avoid asking for business data from your customers and focus can be placed on the actual information that is desired.  Fortunately, it's usually fairly easy to get business data for the customers you plan to survey.  And, by organizing your survey process to take advantage of business data, your surveys can be shorter yet still  effective from an insight perspective while being considerate of customer time.  

Four techniques for incorporating business data into customer surveys

Needless to say, linking survey responses to business data is not a new challenge.  And, companies often go to great lengths to do it.  Larger firms often integrate customer surveys with other systems, so that the information derived from surveys becomes part of the customer record and can then be extracted, aggregated and analyzed along with other customer data via the company's normal reporting mechanism.  But, even in this scenario, data gathering via surveys that are not integrated with other systems (because I/T has to do it on a survey by survey basis) still suffer from the linkage challenge.  So, companies have evolved  four techniques to link business data with customer survey responses.

1. Brute force. In this popular approach (often deployed when using low-end survey tools) a customer list, in a spreadsheet, is developed where business data is included for each individual to be surveyed.  An identifier is "coded" to each individual customer in the spreadsheet. Each e-mail to be sent is also coded with the same identifier (hopefully) to match the data in the spreadsheet.  Most survey tools allow this kind of coding and will "kick" out resulting survey response data in a spreadsheet file. If coded correctly matching up survey responses with business data later is pretty easy.  Reporting can then be done in via spreadsheets or other data manipulation tools.   The downside is that this is a time consuming and error prone process.  Data has to assembled, coding assigned, used properly, re-matched after the survey, then handed off to a spreadsheet guru to generate the analyses and reports.  The time investment often outweighs the cost savings of using a low-end survey tool.

2. The multiple mailing method. This is similar and slightly more sophisticated approach to the brute force method. Instead of coding respondents and then matching responses later, in this method the spreadsheet is filtered in advance by the needed business data.  Each filtered subset is then sent the survey. When responses come in, you already know that batch #1 is from "RegionA large customers", Batch#2 is from "Government accounts in California", Etc. Survey responses organized and sent this way are easy to interpret and report on but hard to do subsequent analyses on.  Needless to say, this method is also somewhat cumbersome in that several or possibly many e-mailings must be set up and scheduled.  And, care must be taken to ensure that no individuals are in multiple subsets (or they'll receive multiple survey invitations).

3. The Customer Panel.  In this method business data is stored within the survey tool in a "panel" (a separate database).  Surveys are sent to panel members and responses are automatically tagged with the information stored about them in the panel.  This is a good approach generally, its only real flaw is that the panel needs to be refreshed or updated periodically so that its business data is relevant.  A second potential flaw is that the survey tools with built in panel support are often at the high end of the market or panel support is an extra cost feature of the tool.

4. Pre-load business data into the survey. In this method business data and customer names are loaded into the survey tool, the survey is designed and e-mailed out.  When responses are received they are already tagged with business data and responses are filterable based on the business criterion loaded to the survey.  Slicing the data becomes fast, easy and fairly painless. If the survey tool has good analytics and reporting tools this approach can save lots of time and provide immediately actionable data for follow up action taking.  It also doesn't require panels, integration with CRM or other systems, spreadsheet gurus for data analysis, and its not subject to data matching errors post survey.

I view method#4 as having the best combination of affordability, flexibility, analytics and reporting power, time conservation for customers and time conservation for the surveying company.   I am not aware of many survey tools that support method#4.  QuestBack is a feedback management system that does.