Sales Intelligence Blog by Lattice Engines

Lattice Engines, the pioneer in big data for sales, today announced the release of salesPRISM 6.0, the latest version of Lattice Engines’ big data analytics platform. salesPRISM 6.0 arms front line B2B sales professionals with real-time, predictive and actionable insight wherever they are using the power of big data.

Big Data for Sales

While the exponential growth of internal and external data has made identifying receptive customers more challenging than ever, big data presents a massive opportunity for sales to drive tremendous gains. The challenge is that reps rely primarily on CRM tools, which were not designed for the world of big data. With so much social networking and internal customer data to sort through, they quickly get overloaded and miss crucial insights.

The salesPRISM big data analytics platform offers the integration of data –both internal and external, analytics, and real-time delivery to alert reps to customer patterns and trigger events wherever they are so they can sell to the most receptive customers at the optimal time.

Comments on the News

• “Big data gives sales the ability to answer the golden questions:  how do I find the customers who are most receptive to my product or service at a given time? What do I say to them? How do I make sure that I am following the best practices of the top reps?” said Shashi Upadhyay, chairman and CEO of Lattice Engines. “The best sales reps already have a talent for this. salesPRISM democratizes this excellence, turning every rep into an A player.”

salesPRISM: The World’s First Big Data Platform for Sales

salesPRISM is unique in its ability to combine massive amounts of internal, external, and Lattice Engines proprietary data to filter the noise and identify patterns through predictive models. This empowers sales organizations with new, dynamic insights and more intelligent targeting.

New salesPRISM 6.0 features

salesPRISM 6.0 harnesses essential insights from the explosion of data to deliver ”engagement opportunities” so sales can interact with a customer when they’re ready to buy, provide warm introductions to reach out to the appropriate contact, and indicate timely content for a relevant conversation based on what’s happening with the customer.

• Enhanced user interface – New UI offers more consistent navigation and the addition of clickable resources to guide users through the application with ease.

• Action prioritization – Combines every action that the rep needs to engage on in one single interface, irrespective of source (e.g., marketing campaigns, analytically generated tasks).

• Multi-channel delivery – Delivers sales insights and triggers to an inbox, CRM system, or mobile device so reps can respond immediately.

• Additional trigger data – Includes expanded triggers from over 50 real-time sources.

• Warm introductions – The Groupodex module leverages the entire organization’s social networks to meet the right potential buyer at prospective customers.

• Seamless Salesforce integration - Seamless syncing of all activities between Salesforce and salesPRISM.

• Management tools – Provides analysts complete control over sales play recommendations, allowing them to tailor processes to meet specific business objectives.

Additional Resources

• For more on Lattice Engines’ approach to big data for sales, please visit http://www.lattice-engines.com/blog/big-data-for-big-sales-how-data-driven-selling-is-revolutionizing-sales-marketing-part-1/.

• For more information on Lattice Engines, please visit www.lattice-engines.com.

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This is a repost of Christine Crandell’s article on Forbes.com. To read the original article, click here.

Jerry Maguire is a legendary icon in the sales profession. While our hero in the movie got the cash, and the girl, there is no romance in the anguish and string of unnatural acts successful sales people do on a daily basis. Yet countless numbers of annual Sales Kick Off meetings have the theme of “Show Me the Money” to motivate their sales forces to ‘work the deal’ and do whatever it takes to bring home the cash.

The firm, Peak Sales Recruiting, has created the infographic to show why top sales people are so hard to hire. The best sales people are masters at relationships, creative problem solving, strategy, lead generation and a good dose of therapist.

To any sales people a truly qualified lead is gold. It’s a simple request of Marketing. Yet that request is often the wellspring from which great animosity and frustration is born. Absent qualified marketing leads, Sales becomes a primordial hunter of two clues: Trigger events that indicate a sales opportunity is brewing, and a way to reach the right person. Jerry Maguire built his business using brute force; identifying a trigger event has been hit or miss. The amount of heavy lifting required to find enough of these clues to fill a salesperson’s pipeline is daunting.

Social media was supposed to take the friction out of selling. Buyers openly discussing purchase decisions with their social graph. Marketing enabling buyers with the right content at the right time. Sales joining the conversation and establishing trusted relationships. But, that is not the way social selling is turning out for most companies. Brands have already caught on that Facebook and Twitter aren’t selling channels. The definition of social selling is evolving and likely will end up being something quite different from what is being imagined today.

What social has actually done is enable Sales to work smarter. Smart drives sales productivity which is the engine of profitable companies. In all the hype around social, a few social selling applications are emerging that actually help sales team hunt smarter.

salesPRISM from Lattice Engines is a cloud application that leverages social technologies to mine clues for emerging sales leads. Based on big data technology, salesPRISM analyzes internal information, external news, and trigger event indicators. It then rates the attractiveness and ease of capture of a sales opportunity. By analyzing patterns embedded in the sequence of events leading up to past sales opportunities then comparing these patterns to current account market behavior, Lattice Engines can highlight how sales professionals should prioritize their time across different opportunities.

According to Shashi Upadhyay, CEO of Lattice Engines, “Our big data analytics engine infers what prospects and customers need based on patterns seen elsewhere.” By bringing together into a single view internal data from marketing automation systems, ERP, etc. and external data from social community sites, websites, news, etc. insightful patterns are identified such as a happy customer, a new office about to be opened, or a company struggling with a failed product. Depending on what you sell, these can be sales clues.

The secret sauce is Lattice Engine’s ability to infer intent. As businesses go about doing their business they leave behind signals that indicate impending trigger events. For example, a company that is planning to open a foreign office will file for an export license, engage in foreign exchange transactions, sign a short term lease, and increase international travel. All these signals are clues that a company is growing and expanding operations. If you sell office furniture, computer servers or accounting services you might want to know about these clues.

Company clues are great but a smart sales person also wants to know the intent of buyers. By looking at the patterns of various buyers within the same organization, Sales can determine not only the inferred intent of the organization but also isolate which buyers Sales should engage with. On the flip side, if buyer behavior doesn’t match company patterns then the probability of a qualified sales opportunity is low. Lattice Engines derives buyer intent through pattern matching at the campaign level with their visiDB and playMAKER products. Using Lattice-Engines, a Fortune 50 computer hardware manufacturer recaptured $750 Million in new pipeline, reduced outbound call volume by 30 percent and increased marketing conversion rates by 45 percent within two quarters. Now, that’s smart selling.

Finding qualified sales leads is one thing; being able to engage with the right buyer is an all too frequent frustration. The ‘key’ buyer is often not in the CRM system. Buyers today are immune to voicemail messages, cold calls, direct mail and other forms of door opening tactics used by sales teams. Waving free box seat tickets to a Yankees game might help but the effort sales go through to get into an account is much like the Greek actor Sisyphus continually pushing his boulder uphill.

The plight of sales can reach a point of desperation. How many times have you seen a sales person send a broadcast email to the whole company to see if anyone knows Jane Doe at XYZ organization? Occasionally the plea for help is read but rarely responded to which is too bad because the sales person has a real opportunity and just needs to find a way into the buyer.

Article continued…

That’s where BranchIt comes in. BranchIt is a cloud application that replaces the desperate email blast with an automated method of discovering who else everyone in the company knows. “BranchIt is a relationship discovery tool,” shares Josh Yuster, CEO and Founder of BranchIt. “It helps sales, HR and marketing get to that untouchable person.”

By mining employee business communications and tapping into corporate email, calendaring, social networks, phone systems and collaboration systems, BranchIt serves as a corporate social search engine. The strength of each relationship is measured along 36 different metrics and scored based on the context and frequency of past interactions. The organization’s corporate social graph is delivered to Sales through their Salesforce.com and Chatter apps, or through a stand-alone social search engine.

The BranchIt corporate social graph is kept current through the continual indexing of new emails, calendar requests, phone calls, etc. Founded in 2004 and grown organically to 25,000 users across almost a hundred organizations, Yuster stressed repeatedly that no personal data is captured or used in the mining process.

Using social technologies to “connect the dots”, as Upadhyay refers to it, is key to selling smarter. But technology is not a cure-all; sales and marketing needs to evolve their processes and mindsets in order to reap the benefits of social. Upadhyay shares his advice for how Sales can work smarter:

1. Consider data as an untapped asset that can drive better customer interactions.
2. Use the Buyers’ Journey to define when the right time is to engage and what the right content is.
3. Improve productivity by “closing the gap” between buyer and sales’ knowledge.
4. Coordinate buyer interactions across functions by aligning teams to the Buyers’ Journey.
5. Retrain sales on how to use signals to find an engagement opportunity.
6. Focus on the individual buyer, not just the company.
7. Assign a Data Tsar to tear down organizational silos and drive cross-functional data usage.

Sales may look deceptively easy from the outside but it can be one of the toughest yet most rewarding careers. In the eyes of your employer you’re only as good as last quarter’s performance and the margin on your last deal. Your customers measure your value by how well, cheaply and quickly what you sold them actually delivers to their expectations.

To survive Sales needs to sell smarter; social tools can be today’s “Help me help you”.

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Big Data is widely acknowledged as the next $100B opportunity. As several observers have pointed out (including McKinsey and the Economist) this wave promises to transform entire industries, enabling a quantum jump in performance and productivity.

What is not so well understood are the many slices of the big data opportunity – specifically how these productivity gains will be realized in individual functions like sales, marketing, HR or supply chain operations.

In this three-part blog series, I will talk about how Big Data is transforming the world of sales into an information science, driving real impact while touching every aspect of the customer experience.

Leading thinkers in the sales & marketing space have realized the importance of this trend:

• Paul Greenberg believes that insight solutions, based on Big Data, will unleash the era of customer engagement
• Esteban Kolsky posits that Big Data will only have an impact if practitioners focus on insight generation by filtering the signal from the noise
• Christine Crandell points out that Big Data is starting to change even simple spreadsheet-based activities like sales forecasting
• Baumgartner, Hatami and Vander Ark’s excellent book on sales growth, highlights the importance of Big Data as one of the most important weapons in a sales leader’s arsenal

But I am getting ahead of myself. Let me first start by recapping what Big Data is, and why it is important for sales professionals.

Big Data is Not About Data

Companies have seen data explode on two fronts. Internally, customer systems like CRM, marketing automation, quoting systems, transaction systems and so on, have become more ubiquitous, more standardized, and more mature. Externally, current and potential customers are spewing massive amounts of data in social networks, blogs, user forums, product review sites, etc. In both cases – internal and external – the data is often unstructured, disorganized and growing at an exponential rate.

Unfortunately, less than 0.01% of this information is useful for discovering buyer’s intent. For a given company, it is possible to find over 1000 attributes for a customer across all the data sources that are available. If you pass all this information to a sales rep, it is entirely overwhelming and completely useless, since the rep would not know what to focus on.

So Big Data is not about data at all – it is about how effective you are at actually gaining insight from data. If you are not generating or receiving insights, you are barking up the wrong tree.

Big Data Democratizes Excellence

From a rep’s perspective, Big Data answers a major question – how do I find the customers who are most receptive to my product or service at a given time? The best reps already have a talent for this. Big Data democratizes this excellence by automating the three habits and skills of excellent reps:

1) A sixth sense when it comes to identifying opportunity: Things change – companies open new offices, win new government contracts, or increase hiring. Some of these changes may be internal – a new financial management system, changes in the network, or the opening of a new data-center. Every one of these changes is an engagement opportunity. Big Data is very effective at identifying these engagement opportunities for the rep. In the era of Customer Engagement, Big Data is the enabler.

2) Saying the right thing: You have to say the right things. A rep doesn’t have time to research and learn what it takes to be effective in every single account. Effective conversations are driven by a deep understanding of the customer’s need and an ability to identify situations where your solution can help solve their problem. Most customers are eager to be educated but they need help bridging the gap between their problem (felt or unfelt) and the solution you offer. Full contextual awareness is the first step towards gaining an understanding of their need. And Big Data can automate this process.

3) Testing and learning: Understanding how each rep is doing against different types of engagement opportunities is key to improving their performance. Leading sales teams will often organize their sales activities around the concept of plays – established targeting and engagement motions that can be measured down to the activity level. Measuring these plays across each stage of the funnel – and adjusting the approach based on results – is key to a successful Big Data program for sales.

It’s All About Generating Insight

There are five steps to generating insights for your sales team:

1) Integrate - Integrate all the (legally) knowable internal and external information about customers and prospects in one place.

2) Identify patterns – Find patterns using machine learning techniques. Patterns for prospecting are often different than those for renewals or cross-selling, so the flexibility to create and manage a large number of predictive models is key.

3) Test & Learn – Where there is no historical reference, point to learn patterns (e.g., new products) and create hypotheses based on your beliefs about markets and customers. These hypotheses can be tested by setting up structured A/B tests in order to learn what is working and what is not

4) Deliver – Integrate systems through CRM so that the prioritized tasks can be delivered to reps and their final action tracked through completion

5) Measure – Set up a system to measure effectiveness. The measurement should include both the soft metrics of engagement (e.g., did the rep act on an engagement opportunity) as well as the hard metrics of performance and productivity (e.g., what was the conversion rate?)

Exhibit 1: Small Data vs. Big Data

In my next post, I will discuss how innovative companies are already using these techniques to derive excessive returns from their investments in sales and marketing efforts.

Meanwhile, if your organization is embarking on a journey to sales excellence using Big Data, we would love to hear of your experiences.

Related:

• [Whitepaper] ‘Smart Sales Reps’ Win in the Age of Information Overload: Six Steps to Sales Effectiveness
• Jerry Maguire Didn’t Sell Smart – Forbes article by Christine Crandell
• Predicting Victory: Using Big Data in Sports and B2B Sales

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The Art of Selling can be time-consuming and complex — sales pros must juggle between prospecting, understanding customer needs, and managing customer expectations. In addition, sales reps must combine all of these elements at the right time to differentiate their offerings from competitors.  However, when this happens, it is a thing of beauty — it is a sale.  The collage of information exchange, the fine weave of activity surrounding a sales cycle, is often referred to as the Art of Selling.

Art + Science: Accelerating the Art of Selling

Normally when one thinks of art, it serves as the antithesis of science. After all, how could the Art of Selling be automated or accelerated? It can. Leading sales executives today are investing in better processes to enhance the productivity of their teams.

The concepts are simple:  help sales professionals receive more information faster and improve the precision of their tools and guidance.  From there, simply let them do what they do best.

Here are three ways leading sales executives are accelerating the Art of Selling:

1) Provide Actionable Insight:  Walk the halls of any modern-day sales floor and you’ll likely witness the “Alt-Tab Problem.”  Today’s sales makers bounce between quoting screens, Hoovers, LinkedIn, Purchase History, Company Websites, and CRM platforms for 10 minutes to 60+ minutes to prepare for a call.  Call preparation is essential to positive outcomes, but today’s CRM applications have failed to keep pace with big data, the myriad of customer and prospect information available to sales teams.

Accelerator:  Integrate 360 degrees of customer information with the abundance of external prospect data to turn call preparation into valuable customer selling time. What would increasing sales productivity by 15% or more mean to your team?

2) Target the Right Prospects:  Sales and marketing organizations once saw prospecting as purely a numbers game, the bigger the pile the better.  Today, those who once sought ways to grow the pile are now faced with demands that can no longer be answered with guesswork and intuition. Executives are recognizing that which companies they allocate prospecting time to, matters.

Accelerator: Use internal data sources (CRM, contracts data, purchase history, etc.) and external data sources (social media, public records, third party data, etc.) to identify customers and prospects most likely to purchase your products and services. Make calculated trade-offs (i.e., incremental sales X likelihood of close) on which accounts/contacts to engage now and which ones to leave for another day. Sales makers with a fair number of high quality prospects have much greater chance of engaging effectively than those sales reps racing to the bottom of the pile.

3) Measure Execution:  With sales pros picking company names out of hat, it is hard to track which methods are working. This leads to a significant gap between sales makers who “get it” and those who are lagging behind, in addition to poor pipeline health and low conversion rates.

Accelerator:  Organize selling time systematically with Plays, segment-specific sales campaigns (e.g., Target customer segments most likely to purchase Product X, Customers who purchased Product X, opened an international office and are likely to purchase Product Y within 6 months). Create and test these Plays iteratively; double-down on successful Plays and remove Plays that are not getting traction. This will provide detailed insight into the behavior, activity and outcomes for each rep.

While it will never be possible to fully automate the art of selling, leading Fortune 5000 companies are leveraging big data analytics platforms to help their teams compete and win. Learn how to harness big data to generate more pipeline opportunity and close more deals, by clicking here.

Are you Accelerating the Art of Selling? Please share your thoughts below.

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SAN MATEO – November 9, 2011 – Lattice Engines, the leader in B2B sales intelligence software, announced today that Andrew Somosi, SVP of Marketing and Business Development for Lattice Engines, will be presenting at the Sales Strategies in a Social and Mobile World Conference on Tuesday, November 15th.

The session, “Social Selling: What’s Really in it for B2B Sales?” will highlight data-driven research on how buyers and sellers are engaging in social media and specific social selling tactics that can boost sales productivity.

“There’s been a lot of buzz and hype around social media for B2B sales. But, to date, there hasn’t been a crisp definition of what exactly ‘Social’ means for the day-to-day activities of sales professionals,” says Somosi. “We look forward to illustrating specific actions that companies can apply to integrate social data and interactions into a comprehensive data-driven approach for targeting and engaging with customers.”

Lattice Engines’ sales intelligence software, salesPRISM, helps B2B sales professionals become more productive. Thousands of reps at Fortune 5000 companies rely on salesPRISM to predict which of their accounts are most likely to purchase and determine which messaging will improve the odds of closing the deal.

salesPRISM combines a company’s internal view of its customers and prospects (e.g., purchase histories, product usage data, customer service records) with external information about these accounts and decision-makers (e.g., news sources, company websites, social media). Since salesPRISM is embedded directly within CRM systems, reps stay focused on the most qualified leads in the pipeline without changing their workflows.

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Six Internal Data Sources to Generate Customer Insight

Inspired by Dave Brock’s post on Sales Intelligence, we began Part 1 of this series by describing the conceptual difference between data/research and sales intelligence: surfacing deeper insight about customer needs. In the spirit of showcasing tangible examples, Parts 2 and 3 of the series will focus on the full spectrum of internal and external data sources available to sales professionals to conduct research. Part 4 will then discuss what it means to distill data and research into insight.

Today’s post (Part 2) is all about internal data. What does ‘internal’ mean? When we talk about internal data, we’re talking about the data that a company (including its employees and systems) generates about its own customers and prospects. Not all of this data is readily available to sales reps, nor is it equally valuable (See the illustrative internal data matrix). The list below is based on ease of access for the rep (highest first). The list is by no means exhaustive, and I invite all of you to add your examples.

1. CRM: Since they’re used daily by reps, accessing CRM systems is a snap. Of course, the value that CRM data provides depends at least partially on the diligence with which reps have entered account, contact and opportunity information in the first place. Still, with a modest investment in data entry, it’s possible for reps to run basic segmentations (e.g., “accounts with no opportunity created this year”). And I said “at least partially” upfront because sophisticated sales organizations are pushing vital customer and prospect intelligence from other data sources to reps via the CRM system.

2. Marketing Response Data: Related to CRM, is marketing response data, which can encompass website visits, website download activity and responses to outbound marketing campaigns. This data is increasingly integrated into CRM so that reps can track the engagement of specific contacts with the company’s marketing activities.

3. Contract Data: Critical nuggets of intelligence are embedded in the actual (and often lengthy) customer contracts, such as discounts, bundled pricing deals and specific service level commitments. The downside is access. Companies have made great strides to digitize contracts. However, the content is still not always easy to search and reps still spend considerable time flipping through the (digitized) pages to find the relevant information.

4. Customer Service Data: Understanding when and why a customer calls for support generates insight. On one hand, you may want to avoid initiating a sales cycle with a customer that’s currently having a lousy sales, implementation or customer service experience. On the other hand, inbound calls can often reflect an underlying customer need. Maybe that recent request for a new password indicates an organizational change you should be aware of. No wonder that some organizations generate 30% of their leads through internal referrals from customer service agents.

5.Customer Purchase Histories: Before you can predict what a customer will buy tomorrow, you should understand what they purchased in the past. Savvy reps can recognize purchase patterns that reflect a likely future need for another product. You’d think that understanding what customers have already purchased would be a relatively straightforward exercise. Yet, complexity can easily creep in. For example, the rep’s view of the account in CRM may not correspond exactly to the way the business bills the customer (e.g., maybe it bills three different locations). Perhaps different products might be billed from different, non-consolidated systems. Or, customers might transact so often that viewing line-item activity is simply not meaningful. But since this data is so valuable, I am not surprised seeing reps diligently taking the extra time to view this data in legacy 1980’s green-screen systems.

6. Product Activity: Many companies are fortunate enough to sell products that ‘call home.’ This means that they send signals back to the company on customer usage trends. A simple example might be a color photocopier designed for 10,000 color copies per month. The copier would send back actual usage data on an ongoing basis. If the usage reaches 15,000 copies, the rep should proactively engage on up-selling the customer on a higher-volume machine. If on the other hand, the data comes back indicating 6,000 Black & White copies, this would signal a mismatch between the product and actual customer needs. Most people are surprised to learn about the breadth of products that ‘call home,’ including hardware, software, credit cards and other payment solutions, payroll systems, online information services, etc. This is one of the most valuable sources of insight for reps, albeit somewhat more difficult to access.

We invite you to add other internal sources you’ve used to conduct research and generate customer insight. We look forward to hearing the specific examples of how you used the data and what you learned to improve your engagement with customers and prospects.

<< Part 1 Part 2 Part 3 Part 4 >>

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Sales Intelligence software leader selects Sequoia Capital as its newest partner

Lattice Engines, the market leader in B2B sales intelligence software, announced today that it has selected Sequoia Capital—the venture firm that backed enduring companies such as LinkedIn, Google, Cisco, Oracle and Apple—as its partner in enabling B2B sales professionals to be orders of magnitude more productive.

Lattice Engines was founded in 2006 with the insight that the explosive growth of data about companies and purchase decision-makers contained hidden, invaluable intelligence for front-line sales teams. With the right technology, reps would be able to ‘predict’ which of their accounts would be most likely to purchase and what messaging would increase the odds of closing the deal.

“Data-driven decisions yield significantly better and measurable sales outcomes compared to the traditional, gut-feel approach,” says Shashi Upadhyay, CEO of Lattice Engines. “Fortune 5000 companies like ADP, Dell and VMware have experienced double-digit gains in sales productivity within the first year of deploying our software.”

Lattice Engines has encapsulated this vision into its sales intelligence software, salesPRISM. salesPRISM is the first solution that combines a company’s internal view of its customers and prospects (e.g., purchase histories, product usage data, customer service records) with external information about these accounts and decision-makers (e.g., news sources, company websites, social media). Since salesPRISM can be embedded in existing CRM systems, reps can stay focused on the most qualified leads in the pipeline without changing their workflows.

“Simply put, Lattice Engines makes sales reps more productive,” says Mickey Arabelovic of Sequoia Capital. “The company has cracked the code on making predictive analytics applicable across different customers, products and sales motions.   We’re thrilled to be their new partner.”

Lattice Engines is one of the fastest-growing companies in North America, propelled by over 100% growth in salesPRISM revenue. Building on a track-record of strong growth and innovation over the past 12 months, Lattice Engines will use the new funding to:

• Continue product development in proprietary data assets, social sales applications and mobile delivery platforms
• Increase the sales team to cover new vertical and geographic markets
• Expand marketing activities to further Lattice Engines’ position as a thought-leader in sales intelligence
• Educate sales professionals on using social data and predictive analytics to enhance their sales performance

About Lattice Engines

Lattice Engines is the leader in B2B sales intelligence software enabling Fortune 5000 companies to Sell Smarter and achieve double-digit increases in sales productivity within one year of deployment through Intelligent Targeting, Contextual Conversations and Measurable Execution. Lattice Engines software integrates internal, external and Lattice Engines proprietary data to identify customer patterns and predictive events that influence buying decisions. Lattice Engines is headquartered in San Mateo, with offices in Austin, Boston and New York. To learn more about Lattice Engines visit
www.lattice-engines.com.

About Sequoia Capital

Sequoia Capital provides venture capital funding to founders of startups who want to turn business ideas into sustainable companies of enduring value. As the “Entrepreneurs Behind the Entrepreneurs”, Sequoia Capital’s Partners have worked with innovators such as Steve Jobs of Apple Computer, Larry Ellison of Oracle, Bob Swanson of Linear Technology, Sandy Lerner and Len Bozack of Cisco Systems, Dan Warmenhoven of NetApp, Jerry Yang and David Filo of Yahoo!, Jen-Hsun Huang of NVIDIA, Michael Marks of Flextronics, Larry Page and Sergey Brin of Google, Chad Hurley and Steve Chen of YouTube, Dominic Orr and Keerti Melkote of Aruba Networks, Jonathan Kaplan of Pure Digital, Tony Hsieh of Zappos, Omar Hamoui of AdMob, and Steve Streit of Green Dot. To learn more about Sequoia Capital visit www.sequoiacap.com.

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In today’s social media driven world, 140 characters says a lot.  People have become accustomed to getting their news and insights in short, easy to comprehend tidbits. For example, I came across a creative blog entry which lists 50 tweet-able tips for graphic designers.  It served as my inspiration for the following list of tips for B2B sales professionals.  I hope it serves as the starting point for further contribution.  Without further ado, I present my nine “tweet-worthy” tips for smarter B2B selling:

B2B Buyers Have Higher Expectations

1. B2B buyers expect sales reps to know more about their business.  Let them know you understand their point of view. Context is key. #sales9

First Impressions Mean a Lot

2. When calling a prospect for the first time, contextual (relevant) messaging is 1.5x more effective at gaining access. #sales9

Netflix, Amazon and Google Can Predict What Customers Want Next – You Can Too

3. Major B2B brands are using predictive analytics to find the best opportunities and give customers a better experience. #sales9

Sales Intelligence Saves Time

4. Sales reps spend more than half their day NOT selling. Give your reps back some time and integrate sales intelligence into CRM.  #sales9

However…Fewer Meetings Can Mean More Sales

5. Research shows that more time spent in pre-sales planning may lead to fewer but much more productive customer meetings. #sales9

Data Quality Matters

6. 15% of contact information becomes inaccurate within one year.  Keep data valuable by keeping it updated and fresh.  #sales9

Data Does Not Equal Intelligence

7. Sales intelligence means data-driven decision support for which customers to call, what to message, etc. #sales9

Internal Data Matters

8. Would you read a book missing half the pages? A complete sales intelligence solution applies both internal and external data. #sales9

Social Selling is More than Just Engaging – It’s About Learning

9. Research shows that 49% of B2B customers are on Twitter – publishing company news. Make their business your business. #sales9

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When you’re at the grocery store getting beer what else do you buy? Chips and salsa? Soda? Diapers? In the 1990’s an analysis of over 1.2 million Osco Drug store purchases revealed that on Friday evenings people bought beer and diapers together.

Why? One guess is that young parents, unable to spend Fridays at a bar, brought the drinks home. But perhaps underage drinkers coupled various adult purchases together in an effort to avoid getting carded. The hypotheses make sense but the pattern went undetected by simple observation and intuition.

Over the past two decades, data analytics have exposed many previously unrecognized patterns in human behavior. The impact of such insights cannot be underestimated. Retailers, insurance companies, financial institutions, and healthcare providers that capitalized on the findings gained a significant edge in their industries (e.g. Amazon.com recommendations).

At Lattice Engines we are creating technology that uses such analytics to understand and predict the behavior of small businesses. We’re applying those insights to an untapped vertical: B2B sales.

What does it mean if a company has a Twitter handle? Filed for trademarks? Is hiring PhD candidates? Won a government contract? Launched a “green” initiative? Changed the retirement benefit plan? We are discovering patterns in the behavior of companies like never before!

The possibilities increase when we append the data across multiple sources. Recently we analyzed a dataset (made public by the Federal Energy Regulatory Commission) of 500K emails sent by Enron employees. We appended that data to information from third party sources and our proprietary data engine to look for new and interesting insights.

We analyzed email signatures in the Enron set and found length to be a predictor of relative position in business hierarchies. Perhaps this is because managers do not need long signatures when sending emails. The employees know their name and how to contact them.

Such analysis can point to important conclusions about a company’s internal structure and the influence of members in it. Analytics like this provides sales reps with behavior patterns and purchase triggers that simple observation and intuition often overlook.

Here at Lattice Engines we love to play with this kind of data and see what surprising and previously unrecognized insights it can reveal about business dynamics and company behavior.

For more information and analysis of the Enron Dataset visit this site http://www.cs.cmu.edu/~enron/. Please comment and share other interesting ways to slice, dice and analyze the Enron data!

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