Process, process, process… And people, people, people. Is this really what sales is all about? Isn’t there something for the geek amongst us? Well, yes, there is. There are some toys, some sales toys (I know, sorry…). Actually, there are loads and loads of toys! No shortage of new applications targeted at helping sales people. From CRM, big data (yes, in sales too) to predictive analytics and tracking tools, the list is endless. Here is one company that recently caught my attention: SalesPredict. I’ll try to present more companies but I start with this one not only because the technology behind their service is rather cool and similar to technologies I have been selling in the past but also because it helps people in sales. So, it combines two keen interests of mine: data science and sales.
So, SalesPredict. Rather good name and if, as we say here in the UK, it does what it says on the tin, then the company should go a long way. Here is a brief profile and some personal thoughts.
Problems addressed: If you’re familiar with my blog, you know that there are only two reasons why people buy: to move away from pain or towards pleasure. So, what are the possible pains that motivate people to use SalesPredict:
1- Prospecting: It’s tough to prospect and generate leads. It’s absolutely critical but it’s hard, which is why many people don’t do it (but should). SalesPredict doesn’t help identify possible prospects to approach in the same way that, say, IKO does. IKO helps identify the prospects who should be approached using a similar linked data technology. They help you in your prospecting and generate leads. But SalesPredict enhances knowledge about that lead. So they are downstream to a company like IKO. So they are a useful tool for prospecting, probably helping those that don’t like doing it to do it and those doing it being better at it.
2- Merging external and internal data: There is so much data out there both in the internal system (eg: CRM) and external system and databases (including social data) that it’s quite impossible for a sales person to know it all and compute it all to make some deduction. SalesPredict aims to do so. Interestingly, I think they are starting to state they also help to increase retention by providing alerts on who is likely to churn. Whilst this seem to be a new development on the product roadmap of SalesPredict, it would definitely be of great value.
3- Qualification time: It takes a fair amount of time and energy to qualify a prospect. And information is power. One way to obtain information is to have a good sales process and knowing how to ask questions (Voltaire once said: “you should judge a man by his questions, not his answers”). But not everybody has a good process and, as we know, prospects are still lying when talking to a sales person. So, the type of technology that SalesPredict provides, can be a good way to address this problem when dealing with sales leads and provide more information to sales people to qualify better faster.
The tech: the tech is a machine learning technology and actually aggregate a mix of internal and external data to match and enrich contacts. It is based on the concept of linked data and statistically inferring the likelihood of certain events based on others and their relationship. The background of the founders is not in using big data / data science dealing with sales leads. Far from it actually. It is in predicting geopolitical events and epidemics , an expertise they took to apply specifically in sales.
The marketing claims: Nothing wrong with this but here are a couple of statements made by the founders which I have noticed. SalesPredict helps to “fine-tune campaigns and sales pitches to deliver the most effective messages for each prospect “. And their users are “statistically most likely to convert from a lead to a sale”. I would generally agree with this on the simple basis that information is power (hence why it’s good to ask questions). So, having more information upfront certainly help getting better results. I also like the part of SalesPredict message that states it helps to qualify prospect out, in other words make better use of our time.
The downside: [Edit made after this paragraph based on conversation with Yaron, one of the company’s founder] SalesPredict is a statistical machine learning tech (edit: I have found a video of the CTO that present this, go straight to around minute 5 in the video I have added at the bottom of this post). This means their users have to be of a certain size with a certain number of accounts and history. Why? Because machine learning technology needs, well, to learn. And to do so, they need to have a training set. So without a starting point, there is no predictive analytics possible and the prediction gets better as the data the machine is crunching is getting bigger. So young, fresh companies probably can’t use SalesPredict (if you are reading this blog and I assume wrongly, please let me know, I’d be interested to understand better). Of course, that’s not a problem. As we say “horses for courses”. What it probably means though is that SalesPredict probably doesn’t use its own (yet) solution, which again would be fine and fair (again, if I am wrong, don’t hesitate to let me know).
[Edit 1:Yaron was kind enough to contact me comment on the small client issues. Yaron mentions that “we -SalesPredict – are actually using our own product. We have other small customers that have seen significant success with the products.” One of the unique characteristics of our product is it’s ability to deal with small amounts of data.]
Pricing: This might have changed but, in their early days, SalesPredict’s pricing was rather straightforward. $100 per month per sales person using it. As in other start-ups, this might have evolved
[Edit 2: Yaron also kindly shared some details about SalesPredict’s pricing as the article on which I found the details wasn’t correct. Here is the accurate information: “Our pricing starts at $15K and is based on the number of leads, opportunities and accounts that you have as well as on the number of use cases that you would like to cover”]
Where: US only as the self declared target is the US market and will dedicate the recent fund raise ($4Mn) to push their growth there. However, I have noticed that the CTO has actually attended some conferences in Paris. Whilst normally start-ups are about razor focused execution and attending a conference in Europe could therefore be a distraction, it is reasonable to think SalesPredict might be pragmatic and would respond to demand in Europe if such demand was to appear.
What about you then, whether fancy or not, do you have sales tech you use on a regular basis or intermittently?
[Edit: Here is the video I have found that shed some light on, notably, the technology behind SalesPredict. Start around minute 5]
