I found a role that required a deep understanding of data warehouse technology, but applied that thinking to the business aspects of marketing databases. Yes, my teams were still building large scale customer databases – one client had 70 million customer accounts – but my personal work was focused on delivering related business process improvement. To accomplish that, I spent most of my time meeting with client side marketing executives and learning about their needs. As I listened, I realized that I had always paid close attention to how companies marketed to me in both a personal and professional context. I was particularly interested in what happened after I gave my name to a company for the first time. How soon did they follow up? Did it appear that they resold my data? Were they respectful of me and did they honor an opt-out when I registered one? I had always loved database marketing; I just hadn’t realized it until then.

In the years following that realization, I built multiple marketing automation systems, learned how to measure the ROI of marketing programs, developed integrated sales and marketing lead generation programs, and managed global customer data quality at a name brand company. Those roles taught me the ins and outs of CRM Marketing, and from there I felt confident that I could take on any role in the database marketing space.

With that in mind, I was excited when I found my new role. I am building a Marketing Operations team from the ground up at a global software company that focuses on oil, chemicals, and pharmaceutical manufacturing. Marketing Operations is defined many ways, but for me it means efficiently managing marketing resources by improving technology, process, and measurement. Woo-hoo! I know how to do that. I’m excited for this new role, and plan to focus upcoming blog posts on establishing robust marketing process, integrating sales and marketing programs, and marketing automation technology. I’m sure I’ll write about other aspects like yearly planning, reporting/analytics, and of course… data quality.

Please comment if you’d like me to dive further into any of these topics.

1) Cloud Is No Longer The Focus

Last year everyone talked about Governance in the cloud. This year it’s dead. Why? I think it may be that this group, unlike the Sales 2.0, is focused on Enterprise scale monolithic systems. Last year at MITIQIS, many presentations were focused on the cloud impact on large scale information quality programs. This year, it’s all about internal, installed systems. I find this facinating. Did this group try cloud, and not see the value? Or is it that there is still a duality of idealogies: One that prefers to keep things internal, and a second that wants to move their IT responsiblility to SaaS apps?

2) Master Data Management (MDM) Isn’t The Only Solution

I was surprised that among the Information Quality vendors and practitioners, MDM was no longer the focus. Joe Bugajski focused on it, but others merely touched on how they would interact with MDM rather than focus on MDM as the central system in an Information Quality focused environment. This year, many people talked about Information Quality at the system level, and fixing business process and human interfaces to eliminate dirty data at the source. This reminded me of the Data Warehouse to Data Mart paradigm shift of 10-15 years ago. I just felt old writing that.

3) Data Quality is a Dirty Word

“Information Quality” is now in vogue. I was corrected several times in conversations when I mentioned data quality. This is somewhere between a more highbrow way of marketing ourselves, and snobery. I don’t think this matters in the least bit, but others believe it’s more accurate and lends more credibility to our practice. As you’ll notice throughout my writing, I resist heavily the practice of pluralizing the word data. I never write, “data are,” which I believe is gramatically accurate. I feel the same way here. I do “Data Quality” work, regardless of who says that term is wrong. All right… I’ll use it in this post and try it on for size. This is the Information Quality Symposium after all.

4) Free Sources Drive Down R&D Cost

Data is available from government sources and tools are available from open source communities. No surprise there, but there was in increased focus on it here at MITIQIS. Why? Talend, an information quality vendor, builds their tools on the back of those open source libraries. They credited various shared data models, methodolgies and data sources that allow them to shortcut proprietary R&B spend. Trillium also spoke up, and mentioned that they leverage some of the same open-source thinking in their full price solutions.

5) 60-90% of Operational Data is Valueless

I won’t say worthless, since there is some operational necessity to the transactional systems that created it, but valueless from an analytic perspective. Credit to Kirk Amidon for this insight - he attended the session where this stat was quoted. Similarly, Steve Adler from IBM and others discussed it in their presentations. Data only has value, and is only worth passing through to the Data Warehouse if it can be directly used for analysis and reporting. No news on that front, but it’s been more of the focus since the proliferation of data has started an increasing trend in storage spend. That wasn’t discussed at the conference… just my opinion.

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.

What is Sales 2.0? I’ve already tried to answer that question once, but let me give it another try. Sales 2.0 is a change to people, process and technology that allows sales and marketing teams to do their jobs in a more intelligent way. It is either very customer or productivity focused (depending on who you ask), but probably not both at the same time.

The theories presented and tools demoed were mostly focused on enabling Sales reps with information that allows them to move closer to consultative selling. However, the final session of the day was defined by the use of ConnectandSell, a smarter version of a dialer that allows reps to efficiently communicate with lots of customers. To gain that efficiency, reps are trained to “just start talking” when they hear a beep in their ear. While that may sound efficient and is likely cost effective, it is the furthest thing from Consultative Selling I’ve ever heard of. How can you be consultative when have no idea who you are going to talk to a second before the connect? Maybe I’m missing the point, but this seemed to be contradictory to everything else discussed at the conference.

Some highlights from the agenda:

Polly Sumner, Salesforce.com’s chief adoption officer was a facinating person to listen to. Polly is a veteran of several of the technology giants and is now helping SFDC get into more places. She is passionate about the technology, and couldn’t wait to demo an iPhone version of the app to an eager group. Her description of “Chatter” led me to proclaim operational sales reporting’s death. I also came to the conclusion that SFDC will lead to more tech savvy and analytically focused sales management over time. I’m sure I’m not the first to come to that conclusion.

Polly spoke about SFDC using their own tools and publishing their best practices for all of their clients to grab. While not unique, this approach arms her adoption conversations with real experience rather than Marketing fluff. Polly showed us how she would follow an account, opportunity, contact or sales rep using chatter to understand an account. By doing so, she no longer had to waste an hour with an account review to prepare for a client meeting.

Perhaps the most important thing I learned from Polly was to take an individual focused approach to implementing CRM. Make it simple for an end user to use a couple of CRM / SFA applications, and they will be more likely to ask for more. Present too much at once, and they will be overwhelmed. She also talked about enabling C-Level executives with Dashboards allowing them to see directly into their CRM system, which could be a revolutionary step that disrupts boardrooms in the future. Imagine the CEO having better information than the Head of Sales? That would be exciting to say the least.

Up next in Part 2: My panel on Sales and Marketing and the end of IT!

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.