How Will Big Data Impact Effective Lead Generation for better Conversions?

People are looking for information (read products and services) all across the web. You, as a salesperson might have an offering but the problem is - what are the chances that the person interested in it will find you and reach across to you? Frankly, the chances are quite less. So what do you do to increase your chances to make a sale? Well, obviously the best thing you can do is to find and reach across to that person before he decides to give his money to someone else. But how to do that? Traditional lead generation methods are only so effective as to give you an excuse of an alternate to shooting in the dark. The generated lead data is limited, the windows are short, the targets are big, the work is harder and the results are uncertain. The conversion rates can well be compared to the conversion rate of a toiling army of bees for one drop of honey.

A decade ago, most salespeople would agree that the traditional methods only took them so far in terms of conversion rates. The data was too limited or redundant and took too long to accumulate but the silver lining, if we can call it that, was that because it was too little, it was easy to process. You got 30 leads, you go and do your salesperson thing with 12 based on some quick prospecting/scoring and depending on how good or lucky you are, you score a couple.

Then five years ago to until recently, salespeople were agreeing that the contemporary methods with the power of web and social media, brought improved capabilities in data acquisition and reach but still something was keeping them from milking that cow. You’d think with all that talk about shrinking degrees of connection, businesses increasing their online presence and all, you’d be better off than mere 3% growth.

Yes, something was definitely missing from the picture. And that something was to do with this - “Having access to a lot of data means nothing if you don’t have a way to utilise it...to its full potential.”

Hmm…”utilizing”, people thought. And then they thought of newer ways to do that. New buzzwords started cropping up - Mining, BI, Analytics. But while that was happening, the data kept spawning silently, persistently and exponentially. And by the time the Sales teams settled on their Analytics tools, they found to their utter despair that they weren’t enough anymore to handle the Volume, Velocity and Variety of data that has been piling up all that while. That almost took the whole bang out from the so called data-explosion. Fortunately, that didn’t happen. Especially, in our case, for the Modern Salesperson.

The modern salesperson, despite having the same problems (perhaps even Bigger), are agreeing, either reluctantly or expectantly to one thing - that a major paradigm shift in the way information is produced and consumed has been set in motion for some time now, that there is an enthusing buzz in the air and that that buzz seems to hold a Big promise!

There’s lots and lots of data floating around the web holding immense potential information for you as a sales person, if only it can be churned to your benefit somehow. But given the speed at which this data is getting generated and becoming obsolete, even the first step can become overwhelmingly discouraging. That first step is - to capture this huge amount of data in one place. But then, the tougher part comes next -  to make it sensible and actionable. For a salesperson, this sensible and actionable information is what he calls a Lead.

So how does Big Data help or proposes to help? Well to start with, Big Data Solutions solve this problem of getting you actionable leads by helping you with at least four things making your chances to conversion far better than those of that salesman a decade ago. These are:

• Identifying most valuable potential customers and creating windows of opportunities

• Telling you the precise thing to show or say to them when the window opens

• Have the right thing to offer at the right time to your prospect

• Raising right flags at the right moment to generate cross-selling and/or up-selling opportunities 

Companies collect a lot of data through a wide array of channels like mobile, website tracking/analytics tools, contact forms, social media, lists, groups & forums, CRM systems and news feeds. While big companies prefer to use their custom developed or customized Acquisition and Analytics solutions by Big Data analytics providers like IBM (BigInsights), Cloudera and HortonWorks; most companies (SMBs mainly) prefer to source their data from a new breed of service providers falling under DaaS (Data as a Service) category who provide On-Demand industry-wise, rich, hard-to-find-data of personnel who can be potential clients. This data is then imported into organizations CRM systems from where the analytics and further lead nurturing process is taken up. Or some prefer to go for the simplest of the solutions - "Outsource" the whole lead generation process to companies like Technology Sales Leads (www.tslmarketing.com), let them deal with the grind and hope to get valuable leads.

Anyway, let’s take a moment to see how the actual data acquisition works in terms of Big Data in general. Well, it’s usually done using the combination of traditional, contemporary and modern methods using techniques like manual and/or automated web content mining, data scraping, searching, social media profiling and crowdsourcing. This data is usually in an unstructured form and is constantly fed and processed into what we call in Big-Data terminology as data-sets using technologies like Hadoop. 

However (can’t stress this enough), just acquiring a lot of data isn’t good enough, for the simple reason that due to its muddled and voluminous nature, it is of little value in itself. To make some sense out of it requires a lot of sifting through, filtering, consolidating, cleansing and validating. And because this effort requires time, using traditional (slower) approaches, it’s more prone to become counterproductive, especially in case of Sales because from Sales perspective, the long exercise might lead to generating more cold leads than any useful ones, as data keeps coming in and changing at a rapid rate and has the tendency to become obsolete fast.

So it becomes imperative to find a way to do it in a more efficient and productive way. One way to do it by having a tool or a system to do this crunching and churning for you - and giving you a streamlined and consolidated picture of what the above systems are feeding you with. But given the big volume of such acquired data, managing it and running complex analytics queries on it becomes a challenge with traditional RDBM systems. And that’s where the Big Data guys come in. Companies like Oracle, Cloudera, Hortonworks, IBM, Intel, Microsoft, and many others all have identified the potential of a solution to this Big Data problem and have come up with their own versions of Big Data Analytics solutions.

In our graphic, this whole thing is happening at stage 2.

Once you have the targeted leads, the usual Sales Process takes over, the only difference is that since the lead generation, prospecting and scoring has been mostly taken care of by the system, you as a Sales person hit the ground running armed with exact information of who to contact to, what to offer him and when.

One of the big advantage that these solutions offer is the range of Analytics one can perform over a large amount of data in a quick and visual (graphs, charts, tables) way. If we take our case of Big Data application vis a vis Sales Process, the direct implication is the shortening of the traditional long-tailed lead nurturing and lead scoring processes by doing the dirty mining work and handing over targeted insights based on your specific criteria (like industry vertical, company size, company revenue, location etc). This ultimately allows a Salesperson to filter out the weak leads and focus on nurturing only the valuable leads (graphic: Stage 7), the ones which have the greatest chance of conversion to Actual Sales.

The beauty of the system is that at every step, new transactional data (financial, logistical, communications etc) is getting generated and getting fed-back into the system which in turn helps in the process of generating repeat, cross-selling and/or up-selling opportunities. Talk of eating your cake and having it too!

Evon Technologies, one of the best software development companies in India has performed Proof of Concepts for data mining companies with Data-Integration and Hadoop Analytics requirements.