Predictive Analytics: How to Apply Data Science to Your Company’s Sales Process

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mickhollison

predictive analysis interview with Mick Hollison

In today’s interview with Mick Hollison, we talk about predictive analytics as it applies to lead scoring. Mick is the CMO for InsideSales.com and a regular contributing author for Inc. Magazine.

Predictive analytics is a brand new topic for us on the BrightIdeas podcast. Predictive analytics helps you make objective decisions about lead quality based on key pieces of data. This information helps your sales team focus on those leads that have the highest probability of becoming customers.

Listen up and hear Mick explain in layman’s term what predictive analytics is, how it works, who should care about it, and how you can use it.

Listen now and you’ll hear Mick and I talk about:

  • (01:25)  Introduction
  • (05:40) Please tell me about the predictive analytics article you wrote for Inc. Magazine
  • (08:40) Who should care about predictive lead scoring?
  • (09:26) How many leads per month do I need for predictive analysis to be valuable?
  • (11:00) What will predictive analysis give me insight into?
  • (12:45) How does predictive analysis affect the experience of the sales reps daily routine?
  • (15:40) How does the scoring actually get tabulated?
  • (19:10) What advice would you give to people who want to improve their conversion?
  • (23:55) Tell me about one of your biggest mistakes or lessons learned.
  • (28:10) What is the recommended pattern of follow-up for your leads?
  • (32:00) Please tell me about one of your customers success stories

Resources Mentioned

More About This Episode

The Bright Ideas podcast is the podcast for business owners and marketers who want to discover how to use online marketing and sales automation tactics to massively grow their business.

It’s designed to help marketing agencies and small business owners discover which online marketing strategies are working most effectively today – all from the mouths of expert entrepreneurs who are already making it big.

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Transcript

Trent:
Hey there bright idea hunters welcome back to episode number 177 of the Bright Ideas podcast. I am your host Trent Dyrsmid and this is the podcast where we help marketers and marketing executives and entrepreneurs to discover ways to use digital marketing, demand generation and marketing automation to dramatically increase the growth of their businesses.

So if you are one of those folks and you are looking for proven tactics as opposed to untested ideas and just theories for ways that you can increase traffic or you can increase conversions or you can make your sales team more productive well then this is a show that you want to listen to on an ongoing basis. So how do I make on that promise, well in every single episode I bring on a proven expert who has achieved results that are significant. And then I get them to basically unpack all of the strategies and tactics that they and their team used to achieve those particular results.

And this episode is no different. My guest this time around is the CMO of a company called InsideSales.com. His name is Mick Hollison and he has been in the technology space for 25 or so years, worked for some of the biggest brands around. And in this particular episode we are going to talk about something that I haven’t really ever talked about on the show before and that is predictive analytics and in particular as it pertains to lead scoring.

This is kind of like if you’ve seen the movie or read the book Moneyball. So in the old way the scouts, they would go out and they would look at the players and they would make an account of subjective opinion based upon their years of experience and so forth and so on and whether that player deserve to play in the big leagues.

And then Moneyball comes along and the fellow in the movie played by Brad Pitt basically says, “I bet I can apply science to this. And instead of making a subjective decision I can make an objective decision based upon a variety of key pieces of data that is going to make it a much more scientific approach to whether or not that player is going to be successful.”

Well for the purposes of this episode replace baseball player with lead. What do you think would be better? If you got a whole lot of leads coming out on an ongoing basis you really want your sales team to pay attention to the ones that are most likely, based upon a set of criteria, to have a propensity to become a customer, be it easy to get a hold of or want a conversation.

You can do that manually, you can look and do it subjectively. But if you have a large enough volume of leads that becomes impossible to do and that is where predictive analytics and products that are made by Inside Sales can really help you to become much more scientific about your sales process. And folks of course that is where business is going as we get more and more data which the internet and online marketing and digital and all this stuff gives us.

It allows us to become much more scientific. So if that is something that is of interest to you, you are really going to enjoy this particular episode. I am going to get Mick to explain to me (someone who didn’t know a lot about predictive analytics prior to this episode) in layman’s term what it is, how it works, who should care about it, how you can use it, so forth and so on.

In just a moment we are going to welcome Mick to the show. Before I do that, if demand generation, inbound marketing, content creation, content strategy are things that you need help with head on over to GrooveDigitalMarketing.com where you can learn how we can help you because that is exactly what my company does.

So with the little commercial out of the way please join me in welcoming Mick to the show.

Hey Mick welcome to the show.

Mick:
Great, thanks for having me Trent.

Trent:
It is an absolute pleasure to have you here, I got to tell you, after seeing the energy you run your company with at the Dreamforce conference that I was at a couple of months ago, I have been looking forward to this interview for a little while because there’s a couple of things that we haven’t talked much on the show before. Before we get into the nuts and bolts of the interview let’s start off with introducing you to the audience.

So in your own words Mick who are you and what do you do?

Mick:
Yeah, my name is Mick Hollison, I am the chief marketing officer of a great little company based in an area we affectionately refer to as Silk and Slopes Utah called InsideSales.com. I have been with the company about a year and a half now after a long career at a lot of blue chip type of software companies from Citrix to Microsoft and IBM and came upon this really bright CEO here in Utah that had a crazy idea of becoming more scientific about sales and I bought in hook line and sinker and have been promoting it like crazy ever since and loving what I’m doing so far.

Trent:
Terrific. In our pre interview you talked about an article and we are going to kick off our interview by talking about this point. It was an article on predictive lead scoring that you wrote for Inc Magazine and it actually had quite a dramatic impact. Let’s talk a little bit about that as a primer and then we are going to spend some more time talking about what predictive lead scoring is and a whole bunch of things around predictive lead scoring because it is something that I know I am very interested in and I think a lot of the audience is going to want to increase their knowledge in that area.

Mick:
One of the great things that has happened for me since taking on this new role Trent is I’ve become a contributing author for Inc Magazine and I really predominantly write around the areas where marketing and sales most often interact. And having had a background in both professions throughout the course of my career I have empathy and at times sympathy for either side of that great coordination effort that happens between those different organizations.

Back in September (I think it was on the 17th) I issued an article on predictive analytics really being the next big thing for sales and marketing. It was shared incredibly broadly; probably way more so than we anticipated my initial article for Inc ever would be and in fact ended up driving us straight into a few deals which is not something that typically happens from the delivery of that kind of content but in this case people resonated enough with what I had to say that they directly reached out to us and some of those have already turned into business for us.

Trent:
I am embarrassed to say I have not had the opportunity to read the article yet; either you sent it and I missed it or it simply wasn’t sent to me or my researchers forgot so I am at a little bit of a loss. Can you give us a very quick overview?

I guess it bleeds into our next question really. Was the article telling people what predictive lead scoring is as an introductor?

Mick:
Yeah, that is absolutely right Trent. Predictive analytics all up is just using a combination of statistics, data mining and in our case degree of machine learning to predict who will be most likely to purchase your product or services. It leverages the current and historical facts to predict the future. As I laughingly said in the article, it is kind of like Nostradamus or Carnac the Magnificent but without the funny hats [laughing].

The idea behind predictive lead scoring is just to be able to in advance reaching out to a particular prospect or lead to have an idea of their propensity to buy and even go so far as to know what would be the preferred communication mechanism for engaging with that prospect; when, where and how to communicate with them. The article goes into a little bit of depth in describing how that works and ultimately the software that we ended up delivering to help with that.

Trent:
Alright so let’s dive into that a little bit deeper. First off, who should care about predictive lead scoring?

Mick:
First and foremost probably anybody doing my job. So chief marketing officers or anybody in demand generation that is trying to generate higher quality leads for their sales organization should care about it; both marketing and sales professionals should care about it quite a bit. Imagine how much more effective you could be if you actually knew who was going to have more likelihood to purchase and how you should contact and communicate with that person.

That is a great value and interest to both sales and marketing professionals alike.

Trent:
Now do I need to be someone in an organization that is getting thousands of leads per month for this to be really valuable for me or what if I am just getting from my website say fifty leads a month?

Mick:
Yeah, the value goes up with the volume. You are right to assert that there is a greater degree of value in this type of technology in a little bit larger volume type of scenario. With that said even with fifty if you are concentrating your efforts on the ten that matter most you’re still being much more effective than you would be just randomly dialing or emailing through that list of fifty leads that maybe came in from your website.

I’d argue it has value for both but I’d say it probably goes up substantially if you start to have larger kind of numbers in lead volume.

Trent:
Alright, and let me just say folks that if you aren’t getting leads from your website and fifty sounds like a big number, it is not. You can get fifty leads a month really, really easily. We are a small company and we get hundreds and hundreds of leads a month from our site. So I can see that for a good majority of the people who are very likely to be listening to my show this is a topic you probably want to pay attention to and it is one I am definitely not an expert in so let’s keep on asking some more questions.

You mentioned in your comment earlier that it is going to help me to predict who I should be paying attention to, when I should be getting a hold of them, how I should be trying to reach out to them. What are the things that it is going to help me gain insight into?

Mick:
It is a great question, all of our work – we’ve ended up creating a product offering, we call it Neural View and all of our work in Neural View and its underlying engine, which we refer to as Neuralytics, was all precipitated by a research study we did originally all the way back in 2007 but have continued to update it ever since. It ended up showing us a great deal of insights Trent about when people like to be contacted or are most contactable; like what day of the week. It turns out Wednesdays and Thursdays are better days of the week substantially better than other days; and mornings and late afternoons.

It turns out through another research study we did on communication methods that executives prefer to be contacted by email or SMS versus via the telephone. And so all of this research that we had done over the years, we began to sense a number of trends and we said to ourselves, “Wow what if we could build technology that could actually intelligently filter out these types of insights and then place lead scores around them so that sales people were spending more time and energy focusing on the right kind of leads and outcomes?”

That is what we did and that is the kind of product line that we built.

Trent:
Okay so to make this easily digestible for a typical sales rep. Does all this data get boiled down to something as simple as a lead score? So that if I’m a BDR / SDR or whatever, I can look at all my leads, I can sort them (if I’m using your tool) in terms of lead score and pay attention to them in the right order or what does the user experience look like?

Mick:
Yeah, that is exactly right. From an individual rep’s perspective, particularly the one that is using the say the Salesforce CRM platform, right in their list view of the contacts that they are just about to make. They would really see two scores in our case. The first one is called the neural score and the neural score itself is based upon a set of characteristics about propensity to by. So perhaps that prospect is a 92 on their likelihood to buy.

But they would also see a score that we call neural sort and this would sort that particular contact in terms of their likelihood to be contacted right now and what would be the preferred communication mechanism; email, telephony etc.

So while it is great to be able to predict somebody’s likelihood to purchase if you have no idea when and how you are going to get into contact with them it still makes it pretty hard. This takes all the guess work out of that and you get focused score for propensity to buy and for the best way and time to try and contact that individual.

So maybe you’re scheduling an email to go out on Thursday morning to that particular prospect rather than just dialing through all of them in a queue treating every lead as if it was equal.

So if it shows up right in your screen up Salesforce CRM view that you would have for your accounts and prospects.

Trent:
Alright, so one of the things that I don’t like to do in my interviews is make them a commercial for the company that my guest is employed by. So obviously you have a platform that makes it relatively easy for people to do. And if someone wants to do some pieces of lead scoring (like I know a lot of people, myself included use a tool called Hubspot that has got some lead scoring in it). There is all sorts of other tools in the market place.

If I was trying to do some of the pieces of lead scoring to try and get me a little bit better connectivity with the leads that are coming in. What are some of the most important things that I would want to pay attention to or is it simply not possible to do because of the complexity of the number of pieces of data that you are correlating for each lead?

Mick:
Sure, it is a great question and I certainly don’t want to make it a commercial either Trent. To be clear, there are plenty of other companies in the predictive lead scoring business. Companies like Lattice Engines and Infer, Flip Top and Sixth Sense and others, I could kind of keep going. And then there is the traditional marketing automation vendors, the Marketos and Eloquents and you just mentioned Hubspot that do have a top of funnel view of lead scoring as well.

There is a lot of technology choices out there to be had. I guess the real difference between them from my perspective anyway is many of them require that a lot of the variables are manually entered by the customer themselves. In other words you trying to market your podcast or research and content to people need to know what those attributes are in your buying audience and those that are interested in your goods and services.

In our findings some of these are pretty good at that and they can do a manual form of a lead score without really using any kind of technology, just by using the insights of their sales and marketing professionals. But doing it in an automated ongoing fashion where the lead scoring gets better and better as more transactions are being monitored and watched. And making the machine smarter and smarter about updating those scores, that is something pretty unique we believe about what we are doing and the modern day predictive lead scoring tools.

Their using both aided machine learning which is putting in inputs about what makes a good lead and unaided or unassisted machine learning or unsupervised machine learning it is sometimes called.

Where the machine itself kind of like Watson from IBM is getting smarter and smarter as it analyzes more data and more information; our belief is it is some kind of combination of that human element entering the variables and the scientific element of just getting smarter from the machine’s perspective in and of its own right is what makes the right combination for delivering the best possible scoring algorithms.

Trent:
Alright, so let’s use me as an example. And if I’m going down a rabbit hole that is just kind of pointless feel free to cut me off because I’m doing my best to understand.

Mick:
It is great, [laughing] I’m enjoying the conversation.

Trent:
No problem, so I get my 200 – 300 leads per month and it is funny because revisiting my own lead scoring is on my to do list for today. It is one of the things this week that I am working on.

So I look at each individual lead and I’m looking at what company are they from, how big is that company, does that company look like it would one that would benefit from the type of demand generation services that we do, I’m looking at their LinkedIn profile and I’m essentially trying to quantify before I bother following up with them, do
I think these folks need what we offer, do I think these folks can afford what we charge for what we do, and how best should I get a hold of this person.

And so I make kind of an objective – or is it maybe subjective decision on this is a lead that I am going to start to (in addition to the automated sequences that I have which drip additional pieces of content which I think would be valuable for my typical site visitor) I might do some additional manual follow up as a result of my looking at those leads, looking at those three attributes and thinking, “Yeah this one is good and no this one is a waste of time.”

If I don’t want to spend $300 a month to use your stuff (or I think it starts at $125) but if I just don’t want to do that, if I wanted to get incrementally better what advice would you give me on maybe some ways that I can do that?

Mick:
Sure, a couple of things; one is that we believe pretty much anybody can get better just by looking at the data that they already have a bit more scientifically and statistically than they do today. For any of your listeners that have ever watched the movie Moneyball we sort of think of ourselves as the Moneyballers of sales. We are counting cards at the casino as Brad Pitt portraying Billy Beane famously put it. It’s a very different way of looking at things and in that movie’s case baseball scouting look.

But I’d argue the scenario that you just described is a lot like the old baseball scout model where you are using subjective criteria that may or may not be really based on that much science to determine who will and who will not make a good prospect or lead for you.

We believe there is lots of ways to apply science to do this. And what we’ve done is we’ve built a model around five core areas and I would argue that using these five core areas or uristics as we call them would be valuable even if you did the work yourself and manually and you didn’t want to pay us or anybody else a service fee for it.

The first one which you touched on a little bit which is firmagraphic data. That is information of the actual company that the lead or prospect may work for. When was it founded? Has it had a recent round of funding or is it an established publicly traded company? What are its annual revenues? Is it in an industry that I’ve serviced historically quite well?

That is firmagraphic data. The second is about the prospect themselves; that is demographic data. That could be stuff like their gender, their age, the region they’re located in physically.

The third one is geographic data and this is a really interesting one that we found a little stronger correlations in that we would have ever imagined. So this is the physical location of that particular prospect and business, what the weather may be like in that area. It turns up that people are substantially more contactable in inclement weather than they are when it is sunny outside as an example.

Sounds kind of obvious when you hear that stated but it is mathematically true.

The fourth of those characteristics is psychographic data, this is more explicit information about the personality characteristics of that particular prospect in as much as you can glean any of them from publicly available sources.

Then last is sistographic data; what’s happened in the stock market? What is the macro economic climate like? Does this particular client have buying patterns and seasons that follow a certain pattern?

My take would be if you can think of your prospects; your leads and opportunities across these five dimensions and assemble the best information that you can on them and produce a score based upon that; and a lot of this is publicly available and out there whether it is in LinkedIn profiles of the individuals or the publicly available websites of the companies that you are trying to sell to, you can glean a pretty darn good lead score just by looking at things across those dimensions.

But I guess I would warn if you are not thinking about it that holistically you are probably thinking of it like those old school scouts were thinking of baseball players in Moneyball and you are not going to get the best bang for your buck by really focusing on the right leads at the right time.

Does that make sense?

Trent:
Yeah it does and yeah there is no way that I am going to do that manually [laughing]. Not a chance.

Mick:
That is the need for some automation technology [laughing].

Trent:
See folks there is an example of Trent going down a rabbit hole trying his very best not to turn the interview in a commercial and really the line of questioning was totally and completely ridiculous. So if you want to do this stuff use one of the vendors because there is no bloody way that you would get a return on your time from trying to do that manually [laughing].

Mick:
It would be pretty hard to do, I wouldn’t argue with you Trent.

Trent:
Indeed. Alright so here is one of my favorite questions that I do like to ask guests. Tell me about a big mistake you guys made early on, either just in the life of your company or in the design and iteration of your product because we’ve often times learn our best lessons from the biggest skid marks or potholes that we hit?

Mick:
I think there are a couple of really interesting ones there. Because what we do is inherently so data driven and we know so much about the individual sales transactions that we monitor. I don’t think we initially anticipated that there was going to be a subset of the listening or viewing audience that might find the technology a bit invasive or arguably even the word creepy has been thrown out before.

We are very, very smart about contacting people in the most intelligent way; in the fastest way possible. So Trent if you went on to my company’s website right now and filled out a registration form you’d be contacted back inside of sixty seconds with a number that appear to be from whatever local area code you are calling from. Because we’ve already predetermined that people are more likely to answer calls from a local area code than they are from 1-800 numbers or certainly from a blocked location.

We’ve also determined that they are radically more likely to become a lead if you are immediate in your response to that web lead, even going as little as five minutes beyond when that form gets downloaded can have a precipitous impact on your ability to ever contact or close that particular lead. I think we learned early on that we needed to be a little more nuance and thoughtful about how we describe some of this technology because there was a subset of the population that was going to find it a little bit too direct; a little bit too in your face.

Maybe we knew a little too much about them before they were ready to divulge it, makes sense?

Trent:
Well it does because if I’m that website visitor and I’m downloading that top of funnel offer that doesn’t mean I have any interest in your company. It means I have interest in the information that is in the ebook or whatever it was that I downloaded. I would want some time to read the damn thing before I get called by one of your sales people and I might not want to get called by a sales person at all.

Mick:
Absolutely. And so for us even learning the nuanced way to approach that with maybe it’s an email in that first five minutes that offers even further in depth research on whatever the topic was that you had demonstrated some interest in and maybe that was the better path forward. With a name like InsideSales.com I think in the early days of the company, we had a hammer so everything looked like a nail. We would take that type of approach to everything.

I think that we’ve learned for our own use; internally as a customer of our own technology and for expressing it to others that those nuances do exist and there are a lot of offers that are top of funnel and maybe need no gate at all in order for somebody to just go and explore and learn a little bit about your company. As a small example of that we just went completely transparent with our own pricing and packaging which is something that in the previous decade as a company we have not done before.

It’s a learning process for our company and for me as a CMO just as it is for all of your listeners.

Trent:
And so I’m interested in how you guys handle web leads then. So you are blogging like we are and many other people in the world. I’m not looking at one of your blog posts right now but I am guessing that there is probably a call to action at the bottom of them that drive people to a landing page where there is presumably an ebook of some kind that they can download.

If that is the case, what happens behind the scenes once someone downloads one of your ebooks? Obviously there is a series of follow up emails. You’re probably making them additional offers to qualify them and push them further down the funnel; that is kind of like marketing automation 101 but are you calling these people? Does the sales team get involved at all?

Mick:
We typically are calling them and one of the research studies that you can find out on our site is on communication methods.

And we not only recommend a certain one for certain job titles and certain visitors to your website (as I cited earlier maybe email would be a more preferable model for senior executives or for larger enterprises that are interested in your goods and services).

But the study also goes on to actually recommend a rhythm, so there is a recommended rhythm of email, email, call, call, email, voicemail, call, call type of a thing. I am not doing that accurately I’m sure but the recommended pattern that we suggest for having the highest likelihood for being able to contact that potential lead and ultimately to be able to move them further down the funnel as you mentioned previously.

We go so far as to recommend that rhythm to different kind of businesses.

Trent:
I’d love to see that report as I’m sure my audience would. I’m on your site, I’m on the research paper section. Is that the correct section?

Mick:
Yeah, I’ll pull it up myself so I can be speaking intelligently while looking at it and making sure I am pointing everybody in the right direction here. If you look under Resources and Research Papers, let’s go back a little bit because this was done a little ways back.

Trent:
Is it the Lead Generation Method Executive Summary during 2013?

Mick:
That is it, that’s the one. Lead Generation Method Executive Summary would be the one to check out on that front.

Trent:
Alright and folks if you are driving, don’t try and write that down, I’ll put this in the shownotes at the end of the episode.

Mick:
Please don’t, I don’t want to be responsible [laughing]. We got enough of a challenge in this country with texting and driving right?

Trent:
Indeed we do.

Mick:
There is another from July of 2014 that goes a little bit more into detail around optimizing business communications that I highly recommend as well.

Trent:
And that is the most recent one. The 2014 Lead Response Report?

Mick:
No it’s July 2014 Research Report: Optimizing Business Communication.

Trent:
Okay.

Mick:
Second from the top, at least in my view.

Trent:
Alright so we have a little bit of time left. What do you think (because you know more about this stuff than I do) if you were interviewing you and you wanted to produce the most glowing helpful interview ever, is there anything that you would ask yourself Mick that I haven’t asked you yet?

I have a promise with my guests, every time you listen to an episode there is intended to be actionable advice that you can literally put into effect in your business as soon as you’ve finished listening to the episode so with that in mind is there anything else here that you would ask yourself if you were me asking?

Mick:
I think I’d ask probably three big things Trent would come to mind for me. I would want to know a little bit about who the heck the company is that I happen to work for and I’d want to know what would be the tangible results and outcomes from real world customers that have adopted some of this type of technology. And as you can tell it is more than technology, it is business process that often needs to be modified as well in order to take advantage of the technology.

I’d think I’d want to know those three things. A little bit about the company, a little bit about what people could or should expect as business outcomes; and then are there any real world customer examples that are worth mentioning.

At the end of the day I can talk about this until I’m blue in the face but if I’m not putting it in concrete terms that people can relate to as real life customers than it probably doesn’t make a spill of beans of difference to them.

Trent:
Absolutely and actually I am pretty happy that you brought that up because I do love talking about use cases. So think of a customer and let’s talk about them. Give me an example.

Mick:
Yeah, sure. So California Casualty is a really good one for us. They’re in the insurance industry. It is an old agency that has been in the business for quite some time. Outbound selling and cold calling remains a pretty critical part of their business although thanks to LinkedIn I’m not sure anything is truly a cold call anymore. It is kind of a warm call.

They were struggling with who do they need to be targeting, when should they be contacting them, how many times should they try to reach them via variant communication mechanisms and in the end California Casualty ended up adopting a combination of our technologies. A dialing product called Power Dialer but informed by the smarts of this neurolytics platform that I referred to and implementing services like Local Presence that I spoke of a moment ago that the person on the receiving end of the call believes they are receiving something from a local caller.

In the end the results for them were crazy off the hook. They were doing about 40% more quotes largely because they were contacting many more people per day. They had about a 23% increase in conversions of those initial leads into actual closed deals and net net was they had revenue increase of about 12.5% in a pretty short period of time using a combination of these predictive lead scoring tools and communications tools; sales communications tools.

California Casualty is a great example, it is an old industry, it is not some hi tech example where everybody is adopting the latest and greatest of everything and yet in that kind of a climate they were still able to get really fantastic business results.

Trent:
And if I was to summarize everything that they did it would be they got more scientific about their sales process.

Mick:
Absolutely, stunningly more scientific. And one of the things that is fascinating Trent is some of the people justify their acquisition of our kind of technology just so that they can analyze the data a little bit better and have better visibility into what their sales people really are doing with those leads and what is really happening to them. Are they being followed up on often enough?

A piece of research that we did a few years ago showed that people are following up on leads on average about one and a half times. Our science says you need to be following up on them six to nine times. It sounds kind of obvious but when people peel back the layers and can actually see how often they are actually following up on things they are often appalled to find out that they really weren’t taking advantage of some pretty high quality leads.

Trent:
How familiar are you with Salesforce.com?

Mick:
We are very familiar with it. We are in the Salesforce ecosystem. We are a very strong partner of Salesforce.com and both companies use a bit of the other’s technology so they’re a great partner for us and a real important part of our current market.

Trent:
Okay so I’ve recently started to use the app in my business because one of my new clients has it and I just started to use it recently because I am very interested in it, especially after attending Dreamforce. Is there a way (and I’m going way off topic here so if you can’t answer it that is fine). You just mentioned this cadence and number of follow ups that are necessary for a lead. Is there a way to in Salesforce build a premade sequence of say, “Okay I want nine touches to happen to every inbound lead and they’re going to be a call and email and this and the other thing separated by these dates?”

And we’ll call that a campaign of sorts. And then simply having that attached to each new lead so that consistently all of those tasks on all of those on that cadence is attached so to speak to every single new lead that comes in?

Mick:
The short answer to the question is yes but not with Salesforce by itself. And so whether it is us or it is another vendor that offers some similar capabilities and functionality. A combination of Salesforce and one or two of its ecosystem partners would absolutely allow you to set up a campaign like that and have that kind of visibility into what you are doing with every prospect.

Yes it is possible; not with a standalone instance of Salesforce today.

Trent:
Alright, because I looked and I couldn’t find it, so besides yourself, what would be one or two other apps or companies in the Salesforce ecosystem that have that basic level of functionality.

Mick:
On the dialing and communication side there are companies out there like Filosophy and Five Nines that we compete with on a day to day basis. On the predictive analytics side I mentioned some of them like Lattice Engines and Infer. On the gameification side there is lots of companies like Hoopla and Badgeville and so forth. Our difference is we do what you might have to couple together four or five vendors to do on top of Salesforce.

We do that in one what we call the Sales Acceleration Platform. That is our difference maker at least for the moment. These markets move very, very rapidly so I’m sure we’ll have more company competing across all of those dimensions in short order but at the moment we are fairly unique in offering things across those different dimensions.

Trent:
Alright Mick thank you very much for making some time to help educate me as well as the audience on how predictive analytics can improve conversions because ultimately I guess that is the goal. If anyone wants to get in touch with you what is the best way to do that? Just one way please?

Mick:
Yeah, just mhollison@insidesales.com. That is my email address and that is the best way to do it.

Trent:
Alright Mick well thank you very much for making some time to be on the show it has been a pleasure to have you here.

Mick:
Fantastic, thank you so much Trent.

Trent:
Alright, to get to the shownotes for this episode just head on over to BrightIdeas.co/177 and if you enjoyed this episode and want to help me to promote the show I’d love it if you’d take a moment and head on over to iTunes and left a five star rating along with your comments on the show. If that is too much work then you can always go to BrightIdeas.co and just click the pre populated tweet button and that also helps as well.

So if you need help with inbound marketing or demand generation services for your company that is what my agency Groove Digital Marketing is for; GrooveDigitalMarketing.com. All the information you need is right there. Thank you very much for tuning in for this episode. I am your host Trent Dyrsmid. I look forward to having you back for another one soon. Take care. Bye-bye.

 About Mick Hollison

Mick Hollison has over 20 years of experience in technology marketing, product management, and sales. He currently oversees all marketing efforts including public relations, content marketing, paid advertising and website conversion for InsideSales.com. He has also worked with many other companies including Citrix, Microsoft, and IBM. He is an accomplished public speaker who has shared his insightful messages on the business impact of technology with audiences around the globe.

 

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