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Increase your predictive sales IQ with these 5 hacks

Increase your Sales Data IQ with these 5 hacks – Predictive Sales

 

Sales are intuitive Photo

I remember clearly what we used to consider sales intelligence.

 

This was way before tools allowed us to create data driven sales forces and add predictable sales outcomes.

When I had first entered sales as an inside rep for a software reseller a few (ahem) years ago business intelligence was a completely different field and one that was rapidly developing. Back then we used to “pull lists” that marketing had come up, which was really just a compiled list of who we thought were top companies, along with a name, title, and the main telephone number. Rarely did we get an email or a direct number and back in those days the switchboard operator could be your best friend or your nightmare.

Depending on the list type (just purchased or old) my intelligence would typically come in the form of whether the prospect was an active company, and whatever information another rep typed into the system, which was typical and as detailed as CLVM.  I would smile and dial away, hoping that someone, anyone, would pick up the phone and list to my pitch, all the while shivering with an intense fear and anxiety in the back of my mind that they would actually answer, because,  what would I say? I had no idea who they were.

The was when Hoovers was new and the only game in town when it came to intelligence and most companies didn’t have them deployed, so we used scripts and freely available public information on the internet. Scripts where the magic resource that could sell anything to any customer, but they rarely worked as written and were constantly modified because they were generic and did not target the specific customer or their needs. And most companies web presence needed improvement so it was down to guessing and seeing if our German clunker of an ERP system or if you could squeeze out a few details from the receptionist.

The anxiety I felt then and couldn’t describe was from not having enough data to feel comfortable with my conversation. Not knowing who the company was and having limited information on them only added to the anxiety of cold calling someone who may or may not be an actual person I needed and was completely terrifying.

The closest I can describe this would be to pick a random name out of a telephone book, spin the wheel on a product that you would want to pitch them and then do your best.  But this is what we had to work with so we soldiered on and sold some software along the way by seemingly pure grit.

 

Sales have come a long way.

 

salesmodernizationWe are now flooded with data, immense amounts of data at our fingertips. Sales CRM’s, Social Data, Industry data, email tracking, marketing automation, and Professional Profiles, the list goes on and on. As a sales rep, we now have access to some of the most massive amounts of data from a very long list of services that make up the modern day “sales stack”. A group of sales information tools sales reps utilize to add enlightenment to their prospecting and sales efforts.

 

This is great right?

Not Always. Let me explain.

 

Back when software was still sold in boxes, we may not have had the data, but most sales reps times were spent actually selling. I would estimate that ⅔ of our time was spent on the phones, talking to customers, and selling our product. This massive amount of time we spent actually selling forced us to know the product inside and out, and in extension forced us to know our clients so we could get them to stay on the line past the first five seconds.  The rest of the time was typically administrative, which consisted of reports, meetings, strategy on what we would cover on our onsite meetings with them.

Now that we are in the age of massive information overload studies are coming out about how much times sales actually spend selling, and amazingly it’s not very much. Proudfoot consulting via selling power estimates 10%, and Docurated pegs that sales typically spend  ⅓ of their time selling.

Wow.

What are they doing with the rest of their time? If you take the examples at face value you can just imagine a group of lazy internet surfing sales reps occasionally picking up the phone or visiting a client and think that the massive investment you have put into these people has been a complete waste of time.

Between administrative  (reports, forecasting, team calls, deal calls, blue sheet reviews, Vito letters), travel, and trying use the sales stack to get deeper insights into their prospects, sales reps time becomes so administrative they have little time for actual selling. With a revenue number hanging over them and an increasing pressure to perform they may just give up and go into the market blind and start selling with whatever tools they have easily available, which is typically email.

The dirty little secret is most sales reps are not the best data analysts and only use the tools that they can quickly extract value from quickly as they try to understand where their next deal is going to come from and predictive sales is something dreamed about. The most effective and widely used sales tools are typically front loaded “glance tools”, where a rep can extract quick value and insights about a customer or prospect as they prepare for their next call or next visit.

Lack of analytics are expensive in sales

So what happens to all of the tools and reporting system that your company spends so much investment on? They go widely unused. This means that most of your $2,280 investment in technology spend per rep is not being fully utilized.

This also means your massive investment in other tools like marketing automation, business intelligence, and other major investments are being underutilized because sales reps are not using this data in their sales process.

 

So what do you do?


Increase your data IQ with these 5 hacks and get your sales people back to selling.

1. Remove the barriers.

you hired your sales team to educate your potential prospects on the value your software or service and what value this brings. You asked them to be competent on your offering, know their customers and prospects and understand the market dynamics of their vertical or customer base.

We have to remove the barriers that are restricting selling, and a huge barrier is data analysis. Sales reps have more than enough tools to utilize, but these tools should be glance tools to add insightful data after they already have their good to great targets and customer intelligence readily available to them. A dedicated analyst can act as your front-line data aggregation specialist arming the sales team with relevant sales information.

 

2. Use what you have.

Instead of looking outside for the latest shiny tool, use the data that you have in-house first. Sales is a data hungry business, and without the right data, you get salespeople that will use intuition and guesswork to isolate who they think will be their best prospect. If sales is supplied with timely and relevant data it will free them up to form analysis paralysis and let them focus on educating your new prospects on the value of your tools.

The sales stack should be used in a way that a sales organization can get near instant value at any point in the sales cycle, and tools should be in place to add that data value at each step along the way. Research tools are great but we should also add importance to mid and late cycle sales intelligence to make sure that we are utilizing the data we have at the right spots.

 

3. Increase your Sales Data IQ with Metrics. 

It’s time to start peeking under the covers for data you may not be using and rethinking what sales metrics are. Most sales organization are awesome at metrics, but this falls into the data-in category and is rarely used to add value to the sales team outbound efforts.

If you are a metrics driven organization there should always be a comprehensive understanding of why metrics are important based on fact so you can educate the sales team on value, and use metrics in a way to help sales teams. After all, 6 calls to good quality prospects are better than 100 outbound calls to poor quality prospects.

Metrics can help you understand your business and when applied correctly can start to add predictability into the sales cycle. If you know that a certain type of client or deal size has a greater percentage of not closing based on your previous metric data, you should put them into a higher touch category so you can foster that business.

 

4. Look at your sales process.

You’ve invested in the tools and the training, but is your sales process data ready? Most sales teams focus heavily on pipeline and business development efforts and rely on the same process they originally developed with very little change to the recipe. The new over educated buyer along with ever changing buying patterns and new competition should have you looking at your sales process and seeing where you can apply data at each step along the cycle.

We also want to remove data as a barrier. As I mentioned most sales reps are using information as a front loaded information source about prospects which means the rest of the process may not be as data friendly as you need it to be. Sales may not like tracking how many calls they make or adding more and more details to Salesforce but they are absolutely open to having relevant data delivered that will help them close their opportunity.

Adding data to your sales process is not something you can forget any longer, it is a crucial element to maximizing your sales organization’s potential and required to fully understand what’s happening in your sales ecosystem.

 

5. Move toward Predictive Sales

You’ve got lots of data from marketing, sales, support, product, CRM, social sources amongst others. All of this data has amazing insights that are ready to be of value when combined and presented intelligently, so why aren’t you using an aggregated view and the data you already have to predict your sales outcomes?.

The simple truth is that we have layered our sales organization with tool after tool, and after time we have so many tools that different levels of insight it becomes overwhelming to get a consistent view of intelligence. It’s now time to look at aggregating intelligence in a way that can combine relevant data sets to produce predictive views into our business as well as prescribe actions that help our sales organization succeed.

This multi-source customer intelligence data can lead you down a road where you remove the guesswork from your sales process and have a data-backed prescription on who you should be targeting and what the data says the best outcomes are.

Sales is a data-hungry business and one which has been underserved in most sales organizations and sorely needing updating.  More tools or training are typically not the correct answer when we have the resources to turn our sales teams into predictable sales and data-driven sales force by using the massively data-rich environments we have created over the last few decades.

If you polled every fortune 500 company, you know the ones with 10’s of thousands of sales resources, and the ones who spend billions of dollars on sales tools and process improvements how many data scientist are dedicated to their sales teams can you imagine what the number would be? I’m guessing the answer would be fairly low which is amazing considering the data-rich environment we are now selling into. It is crucial we get more data-driven in sales.

 

Omniom is a data-driven sales and process improvement consulting services company located in Phoenix Arizona who specializes in increasing new revenue streams by utilizing data science tools and methodologies.

 

Sean Gately is the founder of Omniom technology group and can be reached at @omniomtech or sgately@omniom.io

https://www.Omniom.io

Join our LinkedIn group @ #datadrivensales 

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The Data Divide in Sales – A Predictive Sales Story

Joey’s a closer.

Every quarter he’s above quota, well above, while the rest of his teams inconsistent at best with only a few guys getting it done in most quarters. An occasional rep lands a huge deal they’ve been working on forever, but nothing so consistent as Joey and his ability to land net new deals, grow existing ones and do it month over month.

His sales manager thinks it’s his delivery style and his VITO letters, his VP thinks he knows how to describe value better and find pain faster than them all, and the marketing manager thinks he is just a born hustler that follows up with every lead and networks with every customer. His co-workers think it’s his amazing territory and getting the best leads and referrals.

Joey has grown consistently important in the sales organization, so important that the team starts to worry that they need to find his magic and reproduce it to the other reps or they could get into trouble. Joey makes up allot of their revenue. Too much. Should they give him more territory, or farm it out to other reps and hedge? How do they reproduce the magic that is Joey? Should they bring that sales trainer back, maybe bottle a little of the magic and spread it to the other reps, regions, and territories? Get on the other reps backs again, monitor and enforce deeper metrics? Maybe they should just promote him to a manager, keep him in the coup…

Decisions.

Sales management is worried because they know that they can count on Joey every quarter, but they ask each rep repeatedly what their gut is, what their commit number is in their forecast, and how confident they are the deals they committed will land. What they can pull in early from next quarter, and ask them to follow up on those dead leads.

Anything, everything to get to that number at the end of the quarter. Hustle. Heads down. Sell.

They’re also stumped because they’ve listened to calls, been with all the reps on-field calls, and monitored every metric that’s important. Calls, visits, lead conversion, touch points, Joey’s consistent but not nearly at the top of the metrics board, not even close actually. How does this guy do it when everyone else is inconsistent?

They worry about the product, they worry about competition, and they worry about the new startups entering their realm and a new generation of buyer.

They’re also worried because they have to add weighted averages on each rep, sales manager, region, and territory because everyone is different and closes different percentages of their overall forecast. Some reps and regions forecast little and sandbag, bringing deals in on the 11th hour other reps have huge forecasts and close little.

They Worry.

The board knows by the time the numbers come up to the CEO and executive management it’s pretty much an aggregation of gut feel, commit, historical averages and hoping they get that one or two big deals to push them over. Nothing the CEO feels comfortable going to the board with, and nothing board feels comfortable advising on and investing in. But, what else can they do?

Standard fare and gut-wrenching

For everyone except Joey. He’s not sitting by the phone or sending last minute emails slashing prices on the last day of the quarter. He’s home talking to Oracle finalizing the management position he’s going to tell you about on Monday, all his deals are in…

This is the Great Data Divide in Sale

Joey’s gifted, without a doubt, but his natural ability to talk to people and his hustle only took him so far. What Joey found out that everyone missed was how to effectively use data to his advantage. That’s right data.

So What’s his Secret?

It turns out while everyone else was worried about the number of phone calls, field visits, emails sent, gut feel, and all the traditional metrics, Joey was applying data science to his sales process. He would routinely run reports and look at close type by industry, isolate past wins and see how many touch points the CUSTOMER made to the website, analyze optimum discount percentage and stand by that, and focus on the verticals that were actively buying.

He would look at percentages of leads that are most likely to close and build a confidence models for this prediction based on data he could readily find from his CRM, Marketing system, and Historical data. He had data no one else was looking at.

This type of deep analyzation of data helped Joey determine when a lead was dead, and where to focus his energy. He also understood while everyone else was running around the country, he could concentrate on the customer base the data told him were most likely to buy.

While everyone else was writing VITO letters to every prospect, he was actively looking at communication tracked from past wins to determine what the prospects were saying, and combined this with industry-specific newsletters to concentrate on hot-button issues. He would then just reverse engineer what they wanted into his email pitch. He kept it simple, focused, and concentrated on data-driven sales, and closed sales.

His customer was happy, his management was happy, and he was happy.

Welcome to the New Data-Driven Sales Organization.

If the above situation sounds familiar it’s because it is. It happens every day in every sales organization across the country. Most organization struggle with the same data driven sales problem, which is, we haven’t historically used data in the most optimized way to extract the value we need to predict better sales outcomes.

Sales, and to that extension sales management is still driven on gut, feel, and passion. After all, sales is a people business, and people are fickle, indecisive and hard to predict. This methodology has molded our sales training and sales processes for the greater part of our history, where gut and feel still rule over data and analytics.

Most often sales use data for tracking purposes, calls, win loss%, reason codes, etc. Most of this data goes in, but very little is extracted from it. And by the time someone cares enough to look, we are on to the next quarter. Sales is a short-sighted business.

Management is forced to use weighted averages, historical data, and a bit of hope and luck to guide them on revenue predictions. Not the best process when what everyone wants is consistent and accurate sales predictions.

As the world unfolds into a digital transformation the sales profession will have to catch up to keep up and actively transform or get lost to competition.

Where metrics of traditional CRM and sales training have ruled before, sales organizations now need greater insight into the what, why’s and how’s than ever before. It must be assumed that every organization needs to be a specialized, know their product and customer, and know how to solution sell and speak the customer’s language, this is the new fundamentals of the professional. We must know their map of the world.

Beyond the fundamentals, sales organization now need to know how to capture and understand data, and then implement that in the sales process. Just like Joey, sales organizations need to understand data from a rep level and be able to communicate and validate this data all the way through and up the sales and revenue pipeline. Things like aggregation of data from sales, marketing, support, and historical records, predictive selling, using outside variables like economic data, should now be the new normal.

This is Big Data and IoT re-imagining the sales process.

Welcome to the new Data Driven Buyer

Buyers are able to walk themselves through most of the sales process without any interaction or sales input, only reaching out when they have already reviewed and researched you and your competitors. How do you sell to an educated buyer?

This new type of interaction requires a different approach. Gone are the times when sales introduced, educated, and controlled the entire sales process from beginning to end and were able to keep out competition based on a relationship. Most buyers are used to multiple proofs of concepts, educating themselves on the players and deep diving into as much information as they consume before they ever contact you.

This new buyer requires sales organizations to think differently and use data in a way that has not previously been deployed. Just as they are going in knowing about your product and service as well as all of your competitors, you now need to know exactly why your customer buy, and then be able to apply data science to actively predict who is the best use of time, the best fit, and dedicate yourself to focusing on those customers first. They will appreciate it, your reps will close more, and you will have better visibility into the sales cycle

The good news is!

The great news is we are at the tip of this transformation, and we’ve been collecting the data we need for a long time. Most organizations have more data than they know how to analyze and are just now putting analysis against this data to see what value they can extract. The sales organizations, along with marketing product and support can actively aggregate and extract value from data and apply it to the sale process very quickly. We can become a data-driven sales force very easily.

It’s time for our sales teams to become less metric was driven and more data-driven

 

 

About Omniom and OmniomIQ

Omniom is an end to end consulting company that helps companies improve their revenue streams by becoming more data driven and designing more efficient sales and channel plans.

Omniom IQ is an end to end consulting and services solution that can help transform sales teams into modern data driven sales forces.

For more information on OmniomIQ and transforming the sales force, visit https://omniom.io/datadrivensales/ or Contact Omniom at Sales@omniom.io

Why Predictive Sales Matter

 

We are at the inception of a massive industry change in sales.

One that is so massive and disruptive it will rival and surpass the last major change in sales, which was the introduction of Software as a Service and the uprooting of traditional Enterprise install-base sales of a decade and a half ago. If you haven’t read our Joey story of what really makes the future amazing sales rep, head over here now.

If you remember the SAAS (r)evolution you’ll also remember that there were many victims in that battle and countless changes in the sales process that continue to affect us today. The SAAS evolution was so massive and disruptive to the sales process it completely changed the way sales organizations go-to-market and left many companies struggling to come up with cloud strategies and sales process for to survive in the new environment.

Salesforce became a billion-dollar company by redefining how business was delivered and introduced a sales concept that was replicated by innovative cloud-based software and services companies, a strategy that would leave many traditional software companies in the dust and struggling to compete, practically overnight. Even today legacy software companies still struggle with producing “cloud ready” applications and are rewriting decades-old software in an effort compete with the software solutions born out of the cloud and revising archaic sales processes in an effort to compete and survive.

I would go so far and say that the innovation, or at least the popularity of solution-based selling, was a direct result of the impact that the SAAS software solutions had on Enterprise software sales. No longer could enterprise sales organizations rely on relationships alone or count the sheer complexity of moving to a competitive solution because it would be too painful to “rip and replace” with something different. SAAS taught us that we needed to know our product intimately, understand our customer, and utilize new sales processes to be competitive in the new cloud marketplace.

We followed that recipe, yet still 15 years later we are still implementing solution-based selling techniques and tools and revising our go to markets plans based on a market that is already shifting in a new direction.

 

 

data driven sales image

 

The advent of data-driven sales will affect everything about how we structure and implement sales strategy today and move us toward the process of creating new business and go-to-market strategies that are focused on the data-driven buyer, as well as have us rethink the competency how much we understand about our prospecting and forecasting reliability.

Forecasting in an of itself is set for a major change, one that moves away from the intuitive aggregation of people data and toward data-driven predictability and reliability.

 

Every area of your sales engine will be impacted because the need is relevant and the technology is in place.

 

You might say we already use a ton of data in our sales process and your right! In my 17+ years of business development and sales experience, we produced a ton of data and most of it was data pushed into some CRM system, but very little relevant data came out. Here’s the dirty secret, in sales we guess A LOT, so much so that we really never know completely why a forecast missed or why were targeting a specific customer, or comprehensively understand why two customers with the same exact need could have dramatically different outcomes.

Most of our data went directly into some CRM system, and most of that data that was delivered back was metrics based churn and burn data that had a low practicality to the day to day job of producing revenue. None of that important data was every analyzed or combined with say, marketing, and support data to give us a better view into what the data is actually telling us about our prospects and customers which are a shame because the data is all there.

selling time image

Analyst’s say that sales reps only spend ⅓ of their time selling, the rest of their time is spent in administrative capacities, travel, or meetings, essentially on selling activities.

The most frustrating part of being in revenue leadership was understanding the why’s and How’s of the business and trying to understand and produce in limited time in a stressful environment.

Why did we lose that deal?

Why did we win that customer?

Why did we miss last quarter’s forecast when our pipeline was so healthy?

How are we going to make forecast next quarter?

How are we going to close X company?

How does our product really compare to X?

 

A sales organization’s time is spent on selling and any deviation outside of that requiring administrative research only hampers the sales organization’s ability to produce numbers at the end of the day. So while sales have a gigantic sales stack of relevant sales intelligence tools they generally still falls back on guesswork and intuition to run the sales cycles and while sifting through limited amounts of marketing lead intelligence produced during the sales cycle. Even more frustrating to sales is that most intelligence happens at the very front of the sales cycle and drops off significantly as the prospect progresses due to marketings investment in lead producing tools.

Predictive Sales Triangle

The issue with marketing as the sole business intelligence engine supplying sales is that almost every organization has adopted a process where intelligence is gathered at the beginning of the sales lifecycle and drops off after the initial stages. Marketing is there to produce leads which they do in abundance and sales is there to follow up and decide where their time is best spent.

Professional animus develops when sales interpret the lead quality is low and marketing fails sales is not following up on leads, often produced by lack of an intelligent view by the sales force. Marketing may have utilized every analytical approach in securing the lead and why that lead is great, but if sales do not see any detail it turns into just another lead.

The Ying Yang between sales and marketing is endless, and the end result is a sale having a very low understanding of the lead practicality and the return to intuitive based selling.

 

What Data Science can teach us.

Data Analysis has been around as long as mathematics although the terms may have changed a few times and finally molded into the latest inception of data science. Originally coined in 1960 by Peter Naur and popularized in 1996 by members of the International Federation of Classification Societies at their biennial conference, data science is the term and application that has recently exploded in the business environment.

Data Scientist just might be the hottest position and most sought-after professional experience in business today. The reason for this is quite simple, with the massive explosion of “big data” and the relevance of the internet of things, there is an abundance of valuable data being extracted by companies to remove intuitive insight and modify processes into data-driven decision making.

The advent of readily available business information data has led to an evolution in every aspect of business and created amazing opportunities to extract value from this data. This along with the massive explosion happening right now with machine learning and artificial intelligence has led the field of data science to be potentially the most relevant advancement in technology in the last century.

The application of data science will change every aspect of our lives and transform nearly every business function. Self-learning machines and software are just the starts because where there were gaps in data-driven business processes data science will certainly add data-driven prescriptive recommendations and changes.

 

Zetabyte of data quote

 

 

How this is relevant to Sales

Sales organizations, for the most part, are one of the least data-driven part of any organization and arguably one of the most critical in need areas for data science. This is largely due to being a revenue center as opposed to an expense center. If you look at marketing, the proverbial sister of sales, you’ll see that systems and software in place to measure and automate most every aspect of lead generation down to fundamental cost analysis metrics. The basics of how much something costs to bring in business and who to target has been refined into marketing because of their expense classification and basically exempt from the sales process.

Marketing is now on the verge of utilizing predictive and advanced analysis of data to target the right people at the right times to maximize lead efficiency. If you look at the latest marketing tools and ad targeting tools you will see a wealth of information being developed to help marketers target the right people. This is partly driven by the prospects themselves and their evolution as a buyer. No longer is acceptable to target semi-random people about your product and service and hope for the best, buyers are more educated and marketers have had to catch up with targeting to make sure they are sending the right message to the right people at the right time.

Sales have been left behind in this data revolution, still relying on simplified metrics and reporting systems that are decades old while utilizing age-old intuitive based approaches to build a sales pipeline and forecasting.

Oddly enough this is not based on any resistance in sales outside of a general resistance to metric-based activities. Sales are screaming and shouting for better data and more intuitive approaches to help them secure more business. These are people who build their lifestyles off of commissioned based selling and are feeling the industry change in front of them while their tools and processes remain the same.

 

Larry Tesler Quote

 

The Next BIG Change

If Software as a Service taught salespeople how to sell customers a solution instead of a product or feature the addition of data science into the sales process will be just as big or bigger.

The industry has already started feeling the impact which started with traditional Enterprise sales and the migration away from large dollar deployments with long sales cycles, and a move toward smaller value based cloud service type deployments. These micro deployments and sales are fueled by SAAS and have shifted the way sales organizations need to concentrate on selling and how they speak to their clients.

The shift has also created the emergence of the ultra-educated buyer. These new buyers have changed the sales process dramatically by educating themselves on products and services long before any sales organization reaches out to them, essentially becoming a data-driven buyer. The way they buy is completely based on analysis and typically very specialized, researching solutions based on a predefined and outlined need, meaning they have mapped out the problem, know the solution and know fairly well who can fix it.

The emergence of the data-driven buyer will drastically change the sales process creating the need for a data-driven sales force

This is compounded by that fact that sales are under enormous pressure to perform and have limited time to produce. With a drastically different sales environment and a new type of data-driven buyer sales intelligence and sales process needs to evolve into a data-driven process.

 

Data-Driven Sales and the emergence of predictive selling

 

Predictive Sales ImageThe intuitive part of the sales organization, which at the moment makes up quite a large segment of the sales process, will need to evolve into a data-centric approach to targeting and educating our prospects. This will require a whole new way of structuring a sales process as well as utilizing data in a way that hasn’t been attempted in most companies.

We see the advent of an in-house data science dedicated to sales as a near-term prediction and the advent of merging data into predictive and prescriptive views as the next logical steps to understand the new buying environment. The eventuality that artificial intelligence-driven sales applications is not that far off, the need to analyze more data than we can see in sales is drastically needed.

We are currently at the point of moving toward creating predictive data-driven forecasts, one where we know the reasons behind the variables in forecasting like why something will close and what deals are at risk, based completely on data. We will understand how to weigh different variables such as utilizing sales data capture systems and combining that data with human variables and other sales intelligence data sources to create data-backed forecasts. This will essentially remove intuitive insight and feel from revenue predictions and add a layer of confidence into a semi-chaotic activity.

Artificial intelligence and predictive analytics will help us understand who we are targeting and why, and what best education and contact methods to inform our prospects. Our analytics will work with us continuously by training off of new data and offering prescriptive advice on where we should spend our time.

Our data-driven buyers will be ecstatic because we will know right away if we can help them and what information to deliver to them, helping them succeed and only engaging in people we feel our product and service can help.

Our sales organization will be delighted because they will finally have the prescriptive data they need to do what they love best, which is to engage and sell instead of being inundated with administrative tasks and data research, an activity that sales are not best positioned to exploit and one where other experts excelled at.

 

The Future is now.

Right now there is a dramatic change happening in the sales industry. Advanced data science is being applied to sales tools, and predictive and prescriptive tools are emerging. We are very new in this evolution cycle and it will take sales organization time to adopt these tools and processes. While I don’t believe a single piece of software will be the answer, the variable of data and process is just too great for a single answer, instead, it will come with small incremental sales process and data capture changes and the introduction of predictive and prescriptive views at many points along the sales cycle.

Here at Omniom, we help companies evolve into a data-driven organization, and are taking the position of utilizing a consulting and services based product approach. Using consulting practices to help transform the sales force and services to incrementally develop a data-driven process.

The time is now to start transforming your sales teams into data-driven sales forces, or you risk the possibility of getting caught in the evolution of data-driven businesses.

 

Sean Gately Founder Omniom photo

Sean Gately is the founder of Omniom Technology Group, a data driven sales consulting and services company.

You can find Omniom @omniomtech or on linked in on the group Data Driven Sales

AI Sales Rep Picture

Is Artificial Intelligence the new Sales Rep

Will Artificial Intelligence Replace Sales Reps?

AI Robot

 

We are in a dynamic age of change with the explosion of artificial intelligence based offerings and the obvious question is how will these new AI-based offerings impact the sales profession?

With each technology advancement we hear the boo birds talking about the end of the sales profession, after all, big data seemed to come and go without much of a direct impact on the sales profession with the exclusion of offering better data, so maybe AI shares the same fate.

Numerous news agencies are already sinking the final nail in the coffin of Big Data with sensational headlines like “Is Big Data in Trouble”, Techcrunch, “Big Data is Dead- long live big data” – InfoWorld or Forget Big Data hype, says Gartner as it cans its hype cycle” – The Register, so does this mean that AI is just another hype cycle?

The point most of the headlines miss is that Big Data is certainly not dead, not at all, it’s actually matured into an offering that lets us leverage all the power data science offers us, and now is the fueling the for the artificial intelligence offerings that will have such a large impact on every area of business, including sales.

Now, don’t get me wrong, I have no fear that sales will magically disappear. Actually, I would say that sales are on the list of the two oldest professions and both will continue to have a strong need well into the future because people need people, but we will see some fairly drastic changes.

 

Sales, after all, is a people business, and AI is well, artificial which puts it at a huge disadvantage until it get’s much better. We are at the earliest stages of AI development and AI is still not very good at human interaction. Just imagine those late night prospecting robocalls you receive and love so much being directed at a CFO for a strategic offering. Yeah, I shudder to think about what his or her impression of the company would be and how any AI-based system could replace a human conversation.

 

 

AI Quote

 

How AI will change sales is more subtle and effectively more game-changing and scary than any sort of robocalling program. AI will sit in the background analyzing massive amounts of data and making recommendations to the sales department on who to call, what to say, and what to do, effectively managing the sales interactions.

And because AI will be able to analyze so much data so fast by utilizing historic and new data streams at near instant speed and making solid recommendations, AI will essentially control the sales process and outsource the human emotional engagement to you. This convergence of AI analysis will have a profound impact on sales because we will essentially follow recommendations from an artificial intelligence on the best methods of selling, but not actually utilizing it for selling itself in the initial stages

Where AI will have a predictable and drastic impact to early sales are any smaller transactions especially if conducted online. I could see AI replacing the need for small business sales reps whose job it is to follow up on small business leads. In this case most of the heavy lifting would be done by the marketing outbound teams and the AI could effectively replace the need for quick interactions and upsell, because AI’s would never forget to ask you need fries with that and would have the data to offer just the right solution based on your buying habits and others like you, and would never get tired.

So the next online chat you have with a sales rep just might not be that kid out of college from Utah and actually might be an AI bot.

It’s going to take quite awhile for artificial intelligence to make any sort of in-roads into the corporate sales process because sales are still so heavily focused on human interaction and relationship building and we just enjoy working with people when it comes to strategic decisions.

AI will ultimately start with smaller micro-transactions where people won’t mind or would rather avoid working with a sales rep and then learn and grow from there into more sophisticated transactions.

A good example of this is Thumbtack.com, if you ever need an event or any sort of local professional the thumbtack AI seamlessly works you through questions, and based on your responses manages the entire sales process without any direct rep ever getting involved. An AI grows and learns this will be more of an accepted norm.

With these changes sales organization will have to dramatically change by adopting the benefits of AI and advanced data science and leverage their human strengths integrated with artificial intelligence data to grow into the new era sales professional.

So while I don’t see any sort of drastic change like AI replacing an Enterprise sales rep, the AI industry will have a profound impact on sales in the near term moving forward.

So your jobs safe, for now.

 

 

Bleep Blop.

Sean Gately is the founder of Omniom Technology Group, a data driven sales consulting and services company.

You can find Omniom @omniomtech or on linked in on the group Data Driven Sales