10 Things I Learned at Sales 2.0 Boston

Over the last couple of days I’ve been reflecting on what I learned at Sales 2.0 Boston. I’m sure some of this has already been discussed in other posts, but I’m interested to hear which of these are most interesting to you.

1) Sales teams are demanding integrated Marketing tools to drive their business.

CRM and Web Analytics can no longer stand as separate systems. Polly Sumner described an experience where she never heard back from an unresponsive CIO, but was able to track that the email she sent was opened 17 times. This implicit interest let her know there was an opportunity at that client. Invaluable.

2) SFDC Chatter allows you to identify top performers.

Eric Johnson described the way his team was using the tool to collaborate and identify the company’s top performers. Eric and Polly both shared experiences that the real superstars of the organization shine through when they analyze their chatter follows and participation.

3) Operational Sales Reporting may not be needed in the future.

This was my most revolutionary “Ah-Ha” moment of the conference. If Chatter allows a manager to see who is taking many actions that drive results, and who is unable to interact with valuable leads and customers, then there is no need to track phone usage, leads closed, and account coverage to understand which sales reps are doing their jobs.

4) You can survive without an IT organization!

I was amazed to hear Dave Fitzgerald from Brainshark describe his systematic dismantling of Brainshark’s internal business systems. Dave sounded very proud when he described the 17 core functions that are now implemented by SaaS tools. He also discussed swapping some out that weren’t performing as expected with simple on / off service contracts. Dave is down to three FTEs supporting his whole Sales and Marketing infrastructure.

5) Siebel is not popular among Sales 2.0 folks.

My company continues to use an on-premise install of Siebel as our CRM / SFA. When I told people this, they gave me a look of sympathy mixed with dissappointment. It was like I had just told them that I had a terminal disease.

6) It takes a village of applications to enable Sales 2.0.

As I begin to think about building a SaaS based Sales and Marketing infrastructure, I realize that you need to select a series of tools that each play their role well. At a bare minimum, an enterprise would need a central CRM / SFA system, a Marketing Automation platform, an integrated lead generation engine, a Sales compensation tool, and an analytic package.

7) The table in the back corner at the Hoovers VIP dinner had more fun than my table.

This was evidenced by the fact that we took the “What will you do to fill the lead funnel?” question seriously, and they spent the same time laughing and drinking. And we still lost to Anneke Seeley’s table!

8 - The Sales 2.0 Conference will be changing it’s name to the Sales and Marketing 2.0 Conference in the future.

As Sales and Marketing Alignment panelist, I completely agree with this approach. The best conversations at the conference were about the intersection of Sales, Marketing, Technology, and Data and over time these things will converge.

9) Sales executives get very interested when you talk about advanced analytics.

That was the number one follow up after my Panel. Everyone I spoke thought they could do better than they were today at priortizing leads, and understood that they needed better analytic tools and models.

10) I need to attend more conferences like this one.

I spend most of my team navigating internal company issues rather than thinking about ways to create revolutionary change for my organization. After attending this conference, I am more qualified to help my company succeed over time. There is no better way I can justify a day out of the office.

CRM and Marketing Measurement to Drive Sales

How do you drive the Sales team to follow up on all those leads you’ve provided? And how do you get your marketing team to provide qualified leads instead of rows of uninteresting data? The answer is to measure both and use the resulting reporting and analysis to find gaps in your marketing and sales processes.

Your marketing and sales systems do what they are supposed to. They keep track of your interaction with customers (CRM) and help your Sales force plan to sell (SFA). They also keep you in touch with your customers through some combination of inbound, outbound, email, direct mail, and other marketing services your company provides. You may have even integrated your social media, web analytics, and online media, but chances are that you have not.

So what’s next? Convergence time.

Let’s start with a basic CRM program and build on valuable layers of information along the way. My company sends out lots of email marketing, so that’s what I talk about more than anything else. Once I’ve executed an email campaign, the first thing I want to look at is the result of any of my tests. Did recipients open emails more frequently when I did A vs. B. Next I want to know whether people clicked through the action buttons I provided them. These first two points are marketing centric, but next comes the fun part.

Once I know who clicked through the email, I have a new segment of interested parties. This segment can be divided up into customers and prospects (based on data available in your CRM system). As a next step, what did those people do when they clicked through to your landing page or site? Did they look at one page and leave? Or follow a path toward a product that you advertised? Or follow a path to a different product? We have now added another level of advanced segmentation from your Web Analytics platform. From a marketing perspective, you can now define lead nurturing programs.

And from a Sales perspective, we have defined richly qualified CRM and Web segments. So what happens when you add a note to your SFA system letting the rep know that a contact or a prospect account has clicked through an email and pursued a specific product? If your marketing team has built credibility with sales reps and management, you can be sure that the rep will trust this information and follow up to drive a sale. If you haven’t built credibility (or communicated this new approach), then the rep will see another bad lead and do nothing.

Either way, you need to report on these cross functional results. When presented Marketing qualified leads rather than bulk leads, what was the action taken by each sales rep. How much revenue was generated for each lead delivered? What about for each lead worked by a rep? If you are able to, you should test delivering different segments to different sales teams to determine which teams are best able to drive results. Maybe inside sales has a better chance to make a qualified lead sale since they are available to follow up immediately when provided a triggered lead. Alternatively, the product path followed online may define the sales rep that should get the lead. Or it could come down to rules of engagement on who gets what.

Once you are able to present segmented results showing which teams follow up on leads and drive sales and which teams let leads sit, you can have better conversations with Sales and Marketing management. This will expose issues with both your Sales and Marketing departments, but can lead to conversations that help both organizations mature. Are your marketing teams communicating well and enabling the sales with the appropriate collateral to sell to these leads? Are your sales reps following the playbook and working the leads the way management thinks they are? Show the results and let the conversation lead to change at your company.

Demographic vs. Firmagraphic Appends

Note: This is a continuation of the B2B vs. B2C series. I will also be presenting some related material at the MIT Information Quality Symposium next week (MITIQS 7/15-7/17 2009). If you are attending, please introduce yourself.

Data Acquisition is an important part of any data driven Sales and Marketing program. I associate the append process with Marketing since that’s where these programs are generally funded, but the clear beneficiary of the work is the Sales organization. And of course, it takes a partnership between Technology, Sales and Marketing to make data acquisition programs successful. A data file on a shared drive or standalone table in a database has little or no value. The data has to be integrated with customer and prospect lists and loaded into the CRM and SFA systems and / or presented through your BI/DW tools to show ROI. Sorry… I got on a roll with the acronyms. They’re defined at the bottom. I’m in a Data Governance role now. Acronyms and definitions are my life (in a scary, scary way).

This raises the topics of Data Cleansing, Address Standardization, Merging & Matching, Deduplication, Archiving, etc. I’ll save those topics for future posts, but would encourage questions in the comments section. It’s fair to say that without a Data Quality focus you won’t achieve the optimal results for either Demographic or Firmagraphic Data Acquisition program.

Demographic Appends

Demographic data is generally used by Marketers and Analysts to determine the best way to target a consumer base. Starting with a universe of customers or prospects, a company can buy information on:

• Credit History
• Purchasing Patterns
• Housing Location and Situation, e.g. owner, renter
• Salary
• Lifestyle / Family

You can also buy data that segments customers based on the provider’s best information. Some is based on geographic of financial information. Others are based in buying patterns. Sometimes they even have cool segment titles like “Boomer Barons,” “True Blues,” and “Jumbo Families.” (All of those are from the Acxiom Personicx family of pre-defined segments). The goal of a demographic append is really bulk segmentation. How do I get enough information about my consumers to segment them for marketing and analysis. In most cases, the purchaser doesn’t care about any single individual or household, other than to get them into the correct program. The marketers are looking at sets of consumers, and then targeting from there.

In very high end consumer sales, e.g., luxury items, high net worth banking etc, you may find cases where sales people will use the appended data at the individual level. But generally it’s used for grouping customers into buckets, finding buying patterns and trends across like customers, and performing analyses such as next best product, lifetime value, and similar. Consumer sales is so transactional, that there isn’t time to research before any one conversation.

Firmagraphic Appends

B2B data, which I prefer to call “Firmagraphic” but have also seen called Firmographic or Firma-graphic, can provide value for not only segmentation, but also for pre-call research. B2B Sales is moving toward a more consultative approach where the sales rep becomes more of a partner with the purchaser. The best sales reps do this across all businesses. Rather than try to sell one product or service (transactional), the sales rep tries to understand the company’s need and deliver a suite of prodcuts & services and sometimes even the workers to use them (in an outsourcing arrangement). I’m sure if you’re reading this you’ve seen the varying styles of transactional and consultative sales reps.

To arm those consultative sales reps with the appropriate information, companies often purchase firmagraphic data and load it into their CRM systems. This data may be grouped into:

• Parent Child Relationships
• Locations of Related Companies
• Contact Information for Executives
• Industry Codes
• Number of Employees
• Revenue

This allows the rep to quickly look at the companie’s situation, and taylor their initial pitch accordingly. “I see you’re in a fast moving industry, with over 100 employees, and that you’re company has decentralized offices across the country. Have you heard of Product A that might meet your needs?” That conversation can only happen to a perspective customer if a firmagraphic append has happened previously. Which reminds me that another form of firmagraphic purchase is the ubiquitous, “Get 200 leads in your target industry,” but that’s not what I’m talking about here.

Segmentation of B2B customers is also sometimes based on Firmagraphic appends,  but as mentioned in the original B2B vs. B2C post, householding in B2B is focused on creating parent child relationships among your customers and prospects. You should also use all of your existing customer information including location, purchasing and servicing history, and past communication response to segment your customers. Once you have those relationships built, you can begin to analyze your coverage of headquarters and branches based on firmagraphic data.

Analytics then focuses on similar models for next best product, lifetime value, likelihood to purchase, likelihood to respond to certain campaigns and others. The tools to d

Acronym Glossary

CRM: Customer Relationship Management. Generally refers to the systems used by Sales and Marketing teams to store and organize customer contact information, purchasing, and servicing history. CRM systems also pump out lots of data used for operational reporting and as inputs to customer analysis and segmentation.

SFA: Sales Force Automation. Tools used by Sales Reps to manage their actitivities. This would include follow ups/reminders, appointments, leads, renewals, etc.  SFA systemsalso includes the operational reporting of those activities in some cases.

BI: Business Intelligence. The analytics and reporting tools built on top of the Data Warehouse. Business Intelligence can also be used to describe the practice of analyzing data to determine important insights and drive strategy. These tools look across CRM, SFA, manufacturing and financial systems.

B2B: Business to Business. Marketing and Sales activities along with associated products and services targeted at business customers.

B2C: Business to Consumer. Marketing and Sales activities along with associated products and services targeted at individuals or households of consumers.

ROI: Return on Investment. A simple calcualtion that takes the difference between the cost of a program and the returned value from it, and divides it by the cost of the program. So if I spend $100 and make $150, my ROI would be the $50 of benefit over the $100 of cost: .5 ROI. People often forget to subtract the cost from the numerator and inflate their ROIs.

Upcoming Blog Posts

June has been a light month for blog posts. I’ve settled on upcoming topics, and even drafted my next couple of posts out. Why the slow month? I took a detour into Lean BI research that proved uninteresting to write about. I’ll scrap that. Gone also is my brief foray into Cloud Computing for BI. I’m just not an expert there. Good to learn about, but nothing I want to associate my name with yet. I also had to knock out a conference presentation for this Summer.

I’ve settled on the following upcoming topics. Bear with me while I get them out there. Enjoy the previous posts in the Data Governance folder. Also, please comment if there are any areas you’d like me to explore.

1) Lightweight Data Governance: A Starting Point

A continuation of the previous post. I’ve finished my MIT Information Quality Symposium presentation for this Summer, and think it would be helpful to write some background on the theory I’m developing. In a recent conversation with a Data Governance colleague, they referred to the work as “different from what everyone else is doing.” I hope that’s a good thing. Either way, it confirmed that the presentation will be provocative for that group. So I’ve got that going for me.

2) Data Quality and Data Governance Blogs I’d Recommend

I’ve been keeping a list of those bloggers I think are really good. I look for people who put their opinions out there, and keep the topic light. I’m also a fan of those who are tool agnostic. Too many in our field are married to their vendors. It’s a bad position to take.

3) Demographic and Firmagraphic Appends

A continuation of my B2C vs. B2B series. In this post I’ll explore where the value is, how to incorporate and whether you should even bother. Have you maximized your own data first? Are there other ways to get access to this data for free? Some podcaster’s I follow think so. More to come in the blog post.

Kaushik’s 10/90 Rule applied to B2B Data

Avinash Kaushik is the leading expert on Web Analytics basics. In his book Web Analytics: An Hour a Day he describes the baseline understanding you need to build and maintain an analytics driven website. I would highly recommend the read. In one section, Avinash describes his 10/90 rule, which he has also posted on his blog, Occam’s Razor. The shorthand version is Kaushik recommends spending 10% on tools and 90% on intelligently trained people to get the most return from your analytics investments.

How else can the 10/90 rule be applied? What about B2B Data? Are you getting the most value from the lifeblood of your outbound customer acquisition strategy? Are you paying too much for leads and focusing on quantity rather than quality. I know I’ve fallen into that trap.

Data Acquisition of B2B Leads

When planning your budget for Data Acquisition, you need to consider not only your list spend, but also the analysts empowered to develop your Leads Strategy. It’s easy to buy a 10MM row list of B2B Leads. All you need is money and a list broker to sell it to you. The more mature model is to understand your customer base and only buy prospect information for companies who have a high likelihood to purchase your product.

My title was previously “Director of Marketing Analytics.” I’m reminded of this daily when vendors call and leave messages for Mark Goloboy, Director of Marketing Analytics. My contact information was gathered from website and magazine subscriptions, webinars attended, and likely my LinkedIn profile. I’m on Jigsaw, Pipl, and ZoomInfo. Those companies gather and sell your data. That’s what they do. If you’re reading this, you are likely on several large aggregated lists that are built from dozens of smaller niche lists. I would recommend googling yourself and opting out of any services that look like aggregators, unless you enjoy hearing vendors’ sales pitches.

But wait. I buy list data. And you don’t want to hear from me just like I didn’t want to hear from you. And therein lies the problem. A vast majority of the leads you can purchase don’t want what you’re selling. No matter how good your sales people are, most of the leads you can provide them will never be sold. So how can you improve results? You need to understand your customer base through analytics, develop patterns of purchasing customers, and only buy those leads who have a high likelihood to purchase from you. That’s easy to say in two sentences, but it requires business analysts with deep understanding of your company and industry, statisticians who know your customer data and can transform it into insightful scoring analyses, and sales and marketing strategists who know how to work with your front line sales people and deliver complimentary messages to your customers.

The 10/90 Rule Applied

So to avoid overpaying for unfiltered B2B lists, you need to follow Kaushik’s rule. If you’re planning to pay $10 for data then you need to assume $90 worth of analytic commitment. That needs to be applied at four different stages.

1) You need to commit to analytics before the list purchase to determine which prospects are likely to become customers. Then you can avoid buying full data sets and instead buy targeted niche lists. Also at this stage you should develop program revenue projections and determine if the list is worth the purchase price. If not. Don’t buy it! Spend the money elsewhere.

2) Once you have the list in house, you need to score it based on previous buying patterns, filter out any existing customers, and prepare the list for distribution to your sales teams.

3) During the program you need to analyze results quickly and course correct if the campaign is not producing results.

4) Following the program you should analyze what worked and what didn’t. Did your models and projections hold up? What was the actual ROI? Was it better for some segments? All of these questions need to drive future programs.

And don’t forget…

Throughout the process, your analysts need to coordinate with Marketing and Sales leaders, CRM and SFA systems owners, and financial strategists to align with other programs and schedules. Following the process communicate with all constituents. Let them know where you’ve had success, and MORE IMPORTANTLY let them know where you can do better. You build credibility if you point out areas of improvement and show the ability to mature your programs.