Enterprise 2.0 Sales and Marketing Track

I spent most of last week in Boston at the Enterprise 2.0 conference where I was honored to be the sales and marketing track chairman.  Next year it will be called E2 Social and will bookend the other conference that has been held in Santa Clara and will become known as E2 Innovate.  There’s good symmetry here.  I can’t think of another purely social show or one focused on innovation.  Most shows today are vendor sponsored which is good but different.

Our track had some cool presentations on social marketing from IDC mavens Gerry Murray and Joe Farentino, revenue performance management from Phil Fernandez, CEO of Marketo, and an intriguing discussion from Pam Kostka, a fellow Crusader and CMO of VirtuOz, a company that makes virtual agents.

If you are wondering, a virtual agent is a software robot that you can talk to regarding sales, marketing or service issues just like a person.  These agents are a happening thing and promise to do away with wait times and improve service.

There were also two panels, one on M&A activity that we put together last minute with the able assistance of Sameer Patel, Josh Greenbaum and Louis Columbus.  As is so often the case with these things, serendipity played a role and caused more than a few people to walk away with the idea that this kind of thing ought to happen again.  Thanks guys, the panel was outstanding and a good example of the talent pool that lurks in the Enterprise Irregulars a group with a low profile (that ought to be greater) and an inversely proportional IQ factor.

The other panel, which I want to focus on, was illuminating to me for an unexpected reason.  I invited some of my brain trust including Thor Johnson, Cary Fulbright, Derek Peplau, Columbus and Murray mentioned above.  Toward the end we had a discussion of big data and someone mentioned a large company that had converted from one CRM system to another and had deleted many years of sales data in the process rather than bring it along and try to figure it out.

Initially I thought throwing away all that data was folly but I came to see it as smart but for reasons that I think are different from the consensus of the panel and audience.  One audience member got the analysis right, in my opinion, when he said simply, “There’s nothing in it,” by which he meant there was a great deal of data but that it was devoid of information content.  How could this be?

Very simply, most CRM systems either have fields or enable you to create them to capture important data like product interest, deal size, projected close date and much more.  All of this is valuable but CRM’s point of failure is that these fields can be overwritten and there is no provision for storing historical information.

Now, you’ve heard my sermon on historical data before most likely.  But at E2.0 I had an insight about the difference between sales and marketing that reflects the difference in the data we collect and analyze in each space.

In marketing we collect data once from a large sample.  If you run a program against a list you collect data from a large number of people one time.  You analyze the data and perhaps discover people who are interested in a product now or in the future and you process accordingly.

Sales is different.  The universe of data sources is smaller but the sources give off data constantly through a sales cycle.  Sales reports — pipelines and forecasts — show a single cross section of the data and they are equivalent to the individual frames of a movie.  Most of the time it’s hard to say much about how a film ends by examining a random frame.  Sometimes you get lucky and the random frame shows the butler with a knife in the in the library etc. and you can make a deduction.  But most of the time you aren’t that lucky.

Unlike the movie, which is a succession of stills projected in rapid succession to give the illusion of movement, the sales forecast is a one and done thing.  Worse, making the report necessarily destroys the old frames.  So, getting back to the company that threw away old data, I would throw it away too.  The old data was simply the last frame depicting the end state of a deal and usually the end state is a loss.

There’s almost nothing you can discover from the end state but if you have all the frames that led to the end then you can apply analytics to it and find out things you didn’t know.  Analytics lets you play the movie back and forth to find the aha! moment.  But you need to keep all the frames.  The point is that in marketing you can apply analytics to a single state of the market but if you try to do the same with sales you’re toast.  Sales data is different from marketing data and so are the ways we analyze it.

In the panel I moderated last week that idea was not in evidence and it shows how we need to re-think and maybe find new people who think differently about selling and sales data.  Without new thinking we’re liable to not be able to figure out the importance of social tools and selling will continue to be a hard nut to crack because it remains more art than science.  It doesn’t have to be that way.

Cloud 9 User Meeting

Forecasting and pipeline management don’t get nearly the attention they deserve and that doesn’t make sense.  Of all the parts of CRM, the forecast is one of the few things many companies still leave to manual systems, i.e. spreadsheets.  Even sales compensation has a higher place in heaven as companies like Xactly have blazed a trail away from spreadsheets to a system with a database and analytics, with excellent results.  You’d think that sales people would be willing to invest as much in the forecast as they do in counting their commissions.

Part of the challenge with forecasting and pipeline management is that some professionals might resent conventional forecasting systems for the same reasons they like compensation systems.  Confused?  You shouldn’t be.  Both types of system reduce uncertainty to certainty as much as possible.  But while that’s a good thing when you are counting existing money (your commissions), it’s a problem when figuring out the future because the future is anything but certain.

That’s why last week’s Cloud 9 Analytics user meeting was so important.  At their third annual user conference, CEO Jim Burleigh, talked about the importance of understanding the probabilities when forecasting.  It’s no coincidence that Cloud 9 now boasts a forecasting user interface that uses probabilities but also acts like a sales manager.

If you’ve spent any part of your career in sales then you know there are deals and there are DEALS.  Some deals are like racehorses, they practically sprint from first call to closure while others plod along and maybe even stop.  That’s an extreme situation and it’s easy to spot the real winner.  But consider two deals at a 90 percent completion stage.  They might look the same numerically but each took a different path to that 90 percent mark.  One might have taken twice as long, one might not have enough money budgeted, one may be run by a C-level officer on the customer side the other might be managed by a director.

These differences in the history of the deal add up and a seasoned sales pro knows they are important.  But conventional pipeline and forecasting tools (e.g. spreadsheets) make no use of history, which might help explain why only nine percent of organizations we’ve surveyed have a 0.9 correlation between the forecast and reality.  The rest?  Foregtaboutit.  When it comes to forecasting these deals, the sales pro might favor one over the other for reasons that add up to gut instinct.  So, it’s no surprise that the pros create three flavors of forecast — the best case, worst case and the most probable.

The genius of Cloud 9 today is that they’ve found a way to take the best of what analytics can do to track history and spot trends and combined it with a forecasting user interface that enables a professional to apply common sense to arrive at best, worst and most probable scenarios.  Some people call it gut instinct and I suppose that’s as good a term as any, but really, it’s not gut — it’s applied intelligence and experience that just happen to be hard to put into words.  At any rate, the new forecasting UI is straightforward and looks easy to use and it will remind professionals of their beloved spreadsheets, but with a lot more intelligence behind it.

Getting sales people to put aside the pure spreadsheet approach and go with something with more rigor behind it may still be a challenge.  But Cloud 9 has demonstrated that it both understands the challenge in all its dimensions and that it can turn its knowledge into very serviceable product.  Like the compensation managers before them, Cloud 9 has replaced the spreadsheet with something that makes more sense, is easier to use and should result in better results all around.

Modeling in the Business Process

Modeling is a big idea and one that I started noodling on many years ago.  In the last couple of weeks I’ve looked at the cloud computing model, or what it ought to be.  Today I am looking at a broader paradigm.  One of the great things about new paradigms is that there is no model per se, in a way a new paradigm is an opportunity to create the model; it’s an incipient model perhaps.

The most interesting models or modeling I can think of are those that take place in four dimensions.  You will recall without much prompting that we live in four dimensions, time plus the three that define space and from this we get Einstein’s space-time.  People who study the big bang speak of matter, space and time as “condensing” out of the event.  That choice of word has always fascinated me.

There might even be more dimensions that we don’t know about or comprehend.  How can that be?  I don’t know the only analogy I can make is that my dog lives in the same four (or more) dimensions as I do but he’s only apparently aware of the ever present now.

Four-dimensional modeling is not hard to comprehend, but like a dog, we routinely fall back a dimension to deal with reality, especially in business.  Let’s use the analogy of riding a bike.  The bicycle stands against a wall in four dimensions like everything else though it can be comprehended in three very easily.  But riding the thing is definitely a four dimensional experience.  You can’t ride a bike unless you make a conscious effort to go through space-time balanced on those two wheels.

Learning to ride a bike requires modeling — either training wheels or the expert hand of an adult or perhaps an older sibling who models for you the feeling of keeping your balance.  No amount of discussion before hand is very instructive for a first time rider because words fail to communicate the feeling in your stomach as you take your first ride.

In business our models are typically three-dimensional.  The two that make the most interesting contrast for me are the accounts receivable (AR) report and the sales forecast.  The AR report tells you in a two dimensional grid about what was done in the one dimensional past.  It gives you an accurate representation of what is owed and what will come in barring some future four-dimensional miscue.

The sales forecast is much different.  We treat is like the AR report but with far different expectations.  The forecast is purely four-dimensional but we insist on treating it like the AR report which, though not perfect, is physics compared to the sociology of the forecast.

My point, and perhaps it is not a big one, is that good forecasting requires a four-dimensional model and that can’t be done with a report.  You might disagree and the evidence is on your side, mostly.  For decades we’ve used a standard forecast report to predict future revenues but honestly, it’s been far less than satisfying.  We get our forecasts wrong quite a bit.  My data invariably shows that sales forecasts rarely have a ninety percent confidence level.  It’s a narrow range — fifty percent is as good as a dartboard so there isn’t a lot of room to work in.  We complain about forecast accuracy with the same frequency we complain about the weather, but as Mark Twain wryly observed about the weather, we never do anything about it.

That standard sales forecasting via reports and spreadsheets has worked so well for so long is not a tribute to the method but an artifact of times when we were able to sell standardized products into huge markets.  Demand was usually sufficient to backfill one opportunity with another when necessary.

But today’s markets are a bit different.  We are doing far more cross- and up-selling than ever.  Product lines are expanding but categories are relatively stagnant.  Getting the forecast right has never been more important because margins are smaller and there are fewer deals with which to backfill.

The solution for the sociology of the forecast might be the same as the solution for the weather — a model moderated by computer processing power.  Rather than focusing on a single report that amounts to a three-D snapshot in time, we need two things.  First, a model that captures past information and integrates it into the present but also the model has to offer enough predictive value from prior experience to enable us to self-correct and avoid a crash.

A child (or a trained circus animal for that matter) on a bike can do this and it should not be terribly difficult for us big-brained adult humans to do so with a forecast.  I have been impressed with the advances made by analytics companies in this area in the last few years though they often discuss everything in terms of analytics.  I would rather they approach this in terms of a model or riding a bike though.  Perhaps that would make the idea of using analytics less daunting.

Thought Leader — Phil Fernandez, CEO, Marketo

Phil Fernandez, CEO, Marketo

Phil Fernandez, CEO of Marketo, is our latest thought leader interview subject on the Beagle website (http://beagleresearch.com).  Phil’s career started in the analytics boom of the 1980s and he’s been successfully bringing analytics closer to the customer with every iteration of a career that includes companies like e.piphany and several others.  Lately analytics has taken on even greater importance as he and other Silicon Valley leaders have begun talking about the importance of embedding analytics in line of business applications.  The shorthand message for all this is, typically, embedded in the movement’s tag line — Revenue Performance Management or RPM.  Who doesn’t like revenue?  RPM strikes a nerve for any CEO worth his or her BlackBerry and that’s is why this interview is a must-read.

Transportation is your new challenge

The cost of business travel is going up and up and up and, oh yeah, Happy New Year.

Forget all the CRM prognostications you’ve been reading over the holidays, the only one of significance to your business and to CRM is what you’ll be paying to get in front of customers.  Last week a former Shell Oil President, John Hofmeister, gave an interview on CNN Money in which he forecasted $5 per gallon gasoline by 2012.

With the national average for unleaded regular at $3.07 last week—a rise of 42 cents over the course of 2010, prices are as high as they’ve been in a couple of years.  This would be good news for an ailing economy because increased energy use goes hand in hand with increasing economic activity.  But at the same time, runaway fuel prices have the potential to shred your SG&A line and tank the economy once again.

This kind of cyclical boom and bust is in the offing unless we get a handle on the transportation costs that are such a big part of front office business processes.  You don’t need to be told this but gas prices, diesel and jet fuel prices move in parallel, which just about defines the travel part of a company’s front office business processes.

The reasons for the rise are well known and follow a classical economic supply and demand curve.  The difference now is that in previous booms you could simply call West Texas, Oklahoma, California, Alaska, Mexico, Norway, Scotland and oh yes, the Middle East and ask them to open the spigots a bit more and all would be well.  Today you can’t do that because supply is at peak and the developing world—China and India but also places like Brazil—all want more energy.  When supply is stagnant and demand rises, so do prices so here we are.

If you’re not a Peak Oil fan, think in these terms—there hasn’t been a new refinery built in the US since the mid-1970’s and refinery capacity is maxed out creating another supply bottleneck.  Also, the cost of drilling in deep water can be as high as a hundred million dollars per well (whether not you discover oil).  That is not the same as the cost of drilling in the bad lands and those costs need to be passed on to the consumer.  You can pick your storyline but it all comes down to the same conclusion.  Travel is becoming more expensive so this is the year to anticipate changing your front office business processes and begin to do something about it.

What’s to do?  Well, much of it comes back to the technologies that mediate front office business processes.  The front office technologies that have been developed over the last decade—and especially the last five years—will come front and center as we craft new and better ways to interact with customers.

Chief among these technologies will be analytics.  You thought I’d say social media or perhaps online conferences, videos or something else?  I will but they aren’t first on the list.  Analytics is first because analytics is the killer application for everything else.  Analytics gives you the ability to make sense of all the data that social media churns up and informs your decisions about which video content to develop and deploy.  It also helps you make rational decisions about which customers to get in front of and when.  So if you haven’t begun dabbling in analytics I’d say yesterday was a good time to start, today is pretty good too.  Tomorrow is iffy.

Next on the list is everything else.  Once you know much more about your customers and, really, demand, you can make intelligent decisions about crafting your messages and putting them into videos and developing online conferences.  None of this is hard to do but it will make your life different.  It will take you off the road and put you on the phone and on the web.

Anneke Seley, co-author with Brent Holloway of Sales 2.0, tells me that some of the most successful companies using new technology are finding ways for marketing and sales to work more closely, breaking down barriers between inside and field sales and developing web and phone strategies where direct field sales was once the order of the day.  I’ll post an interview with Seley shortly.

Thinking differently about front office processes is not hard but implementing new ideas might be.  While we all want to save a buck, investing in new technologies that help do this is a tough call at the tail end of a recession.  Part of Seley’s advice to me is to start with a pilot project to see if a new approach will work in your company with your staff and products.  If success is elusive, think hard about people, process and technology.  Five-dollar gasoline and jet fuel spell a turning point and you simply have to get around that corner.

Next year is a strategic opportunity

Recessions are always a good time to rebuild your competitive infrastructure and the slow growth/recession of the last couple of years has been no exception.  On the stock market, the technology sector seems to be doing quite well.  After bottoming in the middle of the summer the software companies especially seem to be rebounding.  Microsoft, Oracle, Salesforce, RightNow and NetSuite are all gainers.

But the drivers for software acquisition remain what they have always been—improving processes, saving money or making money.  Companies whose products can do one or more of these will do well.  And customers will gobble up their wares as they seek out more competitive stances in their chosen markets.  The theme to watch for is replacement as many foundational applications that were implemented for Y2K reach the end of their shelf lives.  Here are some issues to consider.

• Ten year-old ERP and CRM systems will be more than ripe for replacement.  New business processes and better economics will do the heavy lifting to prove the case for new applications.  Many of the conventional vendors like Oracle and SAP will be there as will newer entrants who’ve proven themselves over the last decade.  Watch for names like NetSuite, RightNow, Salesforce and others to command attention.
• Cloud computing.  After several years of debate about what cloud computing is or is not, customers are in a great position with lots of choices for solutions.  It doesn’t matter whether you prefer single tenant or multi-tenant solutions, the economics of running software in the cloud are so compelling that you can find a vendor that speaks your cloud dialect.  Virtually every front and back office vendor has a cloud offering or two.
• Analytics is another solution set that has been in the background for many years.  But new demands in the form of trying to make sense of the mountain of data brought in daily by our social applications makes analytics a necessary add-on.  Analytics solutions are abundant and even SAS Institute, a pioneer in enterprise analytics, has jumped into the market with cloud based solutions for social data.  It is somewhat surprising that Gartner expects only 35% penetration in customer service centers by 2013.  That looks like a great opportunity for differentiation to me.
• It will also be a year for collaboration and I think collaboration may be the first true business social application type.  Judging from the rapid adoption the Salesforce’s Chatter is receiving I anticipate the broader market will see collaboration as a business process no one can afford to ignore.
• Integration will be important in the year ahead too.  There are no so many applications and application types on the market that we can safely give up any pretense that a single vendor could deliver all of a company’s CRM needs. APIs and cloud computing make integration more important and feasible.  More vendors will discover that the winning strategy is to do whatever is possible to pre-integrate their wares with strategically important foundation CRM vendors.  It wouldn’t surprise me to see some vendors begin to organize around specific business processes or types such as channel selling.
• This also implies that many companies will be looking to extend their solution sets with strategic additions.  Any company can optimize its CRM deployment and probably gain competitive benefit by looking at its business processes and comparing their level of automation with the product sets now on the market.  Need a way to keep your sales people in the game?  Try a compensation management system.  It will give them a way to quickly understand their progress in the only way they keep score.  At the same time it will reduce the back office overhead caused by end of quarter commission calculations.
• If you have an interest in bringing out a new product but worry that a limited marketing budget could limit your success, you might first consider a variety of customer analytics that can help you determine which customers have a need, what that need is and how to approach them.
• Or perhaps you are looking to improve service and save money but worry about displacing the good but expensive handholding your service group provides with faceless automation.  Try a social service solution that engages your user community to help answer basic customer inquiries through Twitter and Facebook.  Not only will you be able to maintain a person-to-person approach but response times might decline and there’s no telling what positive fallout might happen when customers help each other.  If you’re monitoring the chatter you might discover that a core group of customers has great understanding of your product and does a super job of helping out.  The help can also turn into articles for your knowledge base.
• The last area for social penetration might be using solutions to analyze your negatives—to identify instances where customers express their displeasure with you on the Web.  It’s much better to deal with an irate customer than to let their anger fester, but first you have to find them.  Social media and analytics can help and it’s a worthy investment.  Our research shows that even the best companies have their detractors but often a vendor knows little or nothing about a problem.

My analysis

To summarize, the year ahead in CRM will be important for replacing old systems and for integrating new niche applications that sharpen your game.  The costs of these additions will be relatively low due to cloud computing and the nature of some smaller niche applications.  The recession ended in July of 2009 and while it might not feel like a recovery right now, there is ample evidence of improvement.  You can use next year strategically to improve your stance as a recovery picks up steam.  There are good products on the market and vendors are still hungry.  If you miss this opportunity, I think you’ll be saddled with your old and relatively expensive systems for longer than you might like.

 

Social, Analytics and Mobility Will Drive CRM Rewrite

“Call rewrite!”  That’s what they said in the olden days on movie sets when the script needed doctoring.  It’s also what the technology industry metaphorically does about every ten years.  We rewrite much of what we’ve been relying on for information processing because the accumulation of new technologies over the previous decade has made our current batch of gear and applications uncompetitive and relatively expensive.  So say Larry Ellison, Marc Benioff and many others.  So the cycle begins again though when exactly is a tricky thing.

By the looks of this economy the new cycle couldn’t arrive soon enough and thoughtful people are asking what the new world might look like.  Some of us may have been lulled into believing that the ten year replacement itch applied to other departments but not CRM.  After all, haven’t we been steadily accumulating changes all along?  And haven’t new technologies like SaaS, pretty much eliminated this cycle?  Well yes and no.

On-demand, SaaS or Cloud Computing—call it what you will—has done a lot to flatten the technology replacement curve but the reality is that new stuff finds a way to creep into the world and our existing infrastructures don’t always handle the newbies smoothly.  The case in point is Cloud 2.

Cloud 2 is as significant a departure from the norm as CRM or SaaS computing were when they were first introduced.  Driving Cloud 2 are three technologies that we are all very well versed in but which, taken together, add up to the call to rewrite.  Let me explain.

The three technologies aren’t even new.  They include mobility, social media and analytics and they’ve been around for decades in some cases.  The convergence of these three technologies within the CRM suite is driving us to rethink CRM and they have the potential to drive the next economic cycle.

Social media is transforming CRM but so is analytics though we are earlier in that deployment curve and while mobility has been a factor for a long time, the convergence of these factors is something special.  It reminds me of the 1990s.

The ‘90’s saw a wave of productivity enhancement and a long period of growth with low inflation and the two are rarely seen together.  It caused Alan Greenspan, chairman of the Federal Reserve, to speculate that we had entered a new economic era of permanently lower inflation and higher productivity.  With so much evidence around him, Greenspan could be forgiven for this thinking but the laws of economics had not changed and, in fact, they were working as advertised.

Under normal economic conditions, increased productivity—i.e. getting more output from workers—required more input.  More production translated into more people, more machines and more raw materials.  But that didn’t happen in the 1990’s as knowledge workers leveraged technology to increase their output.

The computer automation boom of the previous decade—the 1980’s—was largely responsible for the aggregate productivity improvement.  While individual companies might have been hard pressed to provide a valid ROI calculation for their technology investments, many decision makers knew that without those technology investments, they would surely be left behind.  It wasn’t until the 1990’s that this infrastructure buying spree aggregated forming the productivity boom.

The same kind of situation may be forming right now as three new drivers—social media, mobility and analytics—converge, especially in front office business processes.  As in the prior example, these technologies have been accumulating in our culture and they have become more robust in each passing year.  Social media may be new but its adoption has been significant.  With half a billion Facebook users alone social technologies have become ubiquitous, a key requirement in deploying any new networking technology.

Today mobility benefits from investments in infrastructure by the carriers and in devices by individuals that provide the essentials for using social media.  Finally, analytics have existed for decades but their coupling with social media is a critical turning point.  Social media generate mountains of data that must be analyzed to be useful and studies show that analytics adoption is shadowing social media adoption in business.

So here is the critical point for me—your investment in mobility will be enhanced and your investment in social media will be justified by how well you adopt social analytics.  That’s right, analytics is the last mile in this journey and analytics, if implemented appropriately, will make the other investments look shrewd because analytics alone will give you insight into the data churned up by the other technologies.  Analytics along with the other drivers provide the essentials for Cloud 2 and for a new round of prosperity.  Most importantly, analytics and Cloud 2 move the discussion from the hardware and software to the business process, which is where we’ve been trying to get for decades.

The Economics of Cloud 2: Will It Drive Prosperity in 2011?

There are three relatively new technologies converging to make Cloud 2.  All three technologies have been available for many years, though in less robust forms and with less powerful integration.  The convergence is driven by their ubiquity, low cost and ease of use.  They are social media, mobility and analytics.  Together these technologies offer a future that is vastly different from conventional enterprise information processing served from a traditional data center or from a data center somewhere else on the Internet that made up the backbone of Cloud 1.  Read the full story here.

 

Analytics Is the Social CRM Secret Sauce

A lot of information is coming together this quarter that begins to put new spin on Social CRM.  While we’ve all been busy getting networked in our personal lives and professionally, a huge mountain of data has been accumulating that will make our work in social technology more valuable.

Last week Harvard Business Review released a report sponsored by SAS Institute which shows that while many enterprises are well on their way in adopting various social technologies for business use, the number that also are deploying analytics lags.  I know of at least two other reports that will contribute similar information when they arrive on the scene too.

This disparity between data accumulation and data analytis is temporary because as an organization accumulates customer data without basic analytics most of the data is useless.  If you want to know who your best customers are, it’s relatively easy to get a report that says who bought the most in the shortest period of time.  But with analytics you can also delve into the data to ask questions of the why and why not types and there life gets interesting.

Asking why can often uncover alternatives, things that were or were not done and to examine the root causes.  In finding those causes you can uncover new opportunities, revenue that is there for the taking because you know where and how to look.

Last week in Las Vegas I listened to many smart people from big companies discussing how they used SAS Analytics to gauge customer sentiment, run marketing campaigns and manage the conversations they have with customers.  I learned about millions of found dollars brought to the bottom line because analytics were able to make sense of the data thrown off by each customer transaction.

Now, granted, in a billion dollar company a few million bucks may not seem significant but it’s the easiest money you can make.  There’s nothing to invent, market or sell to get the revenue, it simply comes from doing a job better.  Also, if you happen to be lucky enough to own the P&L for a department using analytics, your growth goal in a challenging economy might look a lot easier to attain with analytics.

Consider the above as playing offense, analytics help with defense too.  According to the Harvard study, most companies don’t know what their customers are saying about them or where (Facebook, Twitter, blogs etc.) they are saying it.  Even my crude research a few weeks ago into using search engines to discover how many customers dislike their vendors, indicates a certain lack of intelligence about the outside world.  If hundreds of thousands of my customers were angry enough to write blogs about my company, I would want to know who they were, but most vendors aren’t at the level of having the appropriate tools yet.

Using analytics to digest customer sentiment and make the data actionable is another way that a company, through reputation management, can potentially earn more on the work it does thus taking some pressure off growth objectives.

So for these and other reasons, social media is building the case for a virtuous relationship between analytics and the data that social media generates.  As a result I see plenty of reasons that analytics will continue to shed its outdated reputation as a technology that is only used by an elite few in an organization.  The big data sets involved also make a strong case for web based analytics processing to help defray the hardware costs, at least for some vendors.

Embedding analytics in the applications and processes—especially those governed by social media—that deal with customers and capture their data will become more important over time.  That’s why it is inescapable to me that analytics will become the secret sauce of a well-run social media or social CRM implementation.  Isn’t there an old adage that says it’s not the data it’s what you do with it?  There should be.

 

Cloud9 and Jim Dickey entertain sales enthusiasts in Boston

I was a guest in the audience yesterday when Cloud9 Analytics came to Boston to meet with customers and talk about the releases that will be part of their offerings later this year.  The presentation lasted a bit over an hour and included presentation of new sales management data by Jim Dickey of CSO Insights and a customer testimonial from Brainshark, EVP, Dave Fitzgerald.

Cloud9 CEO Swayne Hill spoke about the future releases and current status of the company.  The company must be doing a few things right because Hill said they have more than 90 customers now and a 50% revenue increase quarter over quarter.  That’s good news given that it’s so expensive to launch a SaaS company and capital is not exactly overflowing.

Last year was the worst year for VC investments since 1997, if you want to know.  And the industry actually raised less money than it invested and I don’t know how long it’s been since that happened.  Last year was also the year a competitor, LucidEra — another SaaS sales analytics startup — went to the boneyard.  So, long story short, Cloud9’s advances in such a market speak volumes.

We also know that if last year had been terrible it would have been an improvement in most companies.  Jim Dickey, whose company performs an enormous survey of sales and sales management professionals each year was there to talk about his most recent survey and analysis, which is due out shortly.  Without giving away all of Jim’s IP (which I can’t do simply because it is so voluminous) some numbers that blew me away:  Last year the win rate on forecasted deals was 44 percent.  Forty-four percent makes picking red or black look like genius work.  Forty-four percent makes a mockery of the whole forecasting process.  It means you’re better off not forecasting.

But there is more.  In the same year, in the face of an economic tsunami, 86% of the companies studied raised sales quotas.  That’s right, they raised their expectations in the face of overwhelming odds against.  I’m sorry but Tennyson is screaming in my ear about the Light Brigade,

Theirs not to make reply,

Theirs not to reason why,

Theirs but to do & die,

Into the valley of Death

Rode the six hundred.

Eighty-six percent is just about everybody.  Now I can understand if the rise in quota had something to do with layoffs and consolidation of territories but you can’t have it both ways.  If you jettison the underperformers in the face of the tsunami, you can’t simply put their quotas on the backs of others.  If you have a realistic expectation that the quota can be attained, why get rid of some staff to begin with?

But I digress.  Dickey’s big point, which I think is very good, is that too often management flips coins when it comes to forecasting and you can’t completely blame them.  The sheer number of deals in a pipeline and forecast make it impossible to know much about any of them.  That’s why Cloud9 Analytics makes so much sense.

The Cloud9 approach is to manage the exceptions.  If nothing changes in a deal then it is assumed to be on track.  When something does change notifications go out to relevant parties like managers and others who subscribe to a forecast’s or even a deal’s feed.  The whole subscription and feed idea is very Sales 2.0-ish and a good thing to have.

But what Hill spoke of and Dickey gave numerical support for, is the next piece in a sales analytics maturity model that I see evolving.  Hill’s contention is that we already use performance management tools in the back office for things like manufacturing.  For instance, we don’t use spreadsheets to monitor quality or relationships with vendors in the supply chain but too often we do the equivalent in the front office.

Hill’s goal is to make sales performance management as rigorous as other performance management and his road map for additions and enhancements to the Cloud9 SaaS service point in that direction.  All this reminds me of Davenport and Harris’s very good book, “Competing on Analytics” which discusses an organization’s need for an analytics maturity model ranging from tactical to strategic use of analytics to improve performance.  Cloud9 appears to be on an interesting track to help customers do this and their further announcements for this year will be interesting to dissect.

I owe you an analysis of Dave Fitzgerald’s testimonial about how Brainshark is using Cloud9 as well as a broader constellation of tools but that will have to wait.