Using machine learning to predict the leads that close
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Re: Using machine learning to predict the leads that close
#2Which sales leads to focus on? We were in a unique position to answer this because we connect data from marketing tools like MailChimp with CRMs like Pipedrive, plus we track web visits.
Re: Using machine learning to predict the leads that close
#3I like your blog on how you use EDA, but I'm not sure I'm getting the Machine Learning piece. It would be nice if you guys went into more details, but I appreciate how you were able to tie together different data sources and walked ppl through the analysis!
Re: Using machine learning to predict the leads that close
#4I worked previously at a company that was trying to do a predictive analytic, ML on top of Salesforce (to qualify and score leads, generate new promising leads, etc). The task was extremely difficult and from what I saw people were getting some marginal improvements from ML itself. Most companies at the end were interested in basic (but quite hard things to do right) - cleaning, dedupoing, enriching, generating more leads based on ICP, etc.
Not sure if in this case it's something different but my take from the past experience it's hard since data is noisy + closing the deals depends on a human as well and these tools don't take that into account usually.
Re: Using machine learning to predict the leads that close
#5I worked previously at a company that was trying to do a predictive analytic, ML on top of Salesforce (to qualify and score leads, generate new promising leads, etc). The task was extremely difficult and from what I saw people were getting some marginal improvements from ML itself. Most companies at the end were interested in basic (but quite hard things to do right) - cleaning, dedupoing, enriching, generating more…
I hope though there will be an ML product that can do a decent improvement in this space. Even small improvement there brings significant ROI.
Re: Using machine learning to predict the leads that close
#6I like your blog on how you use EDA, but I'm not sure I'm getting the Machine Learning piece. It would be nice if you guys went into more details, but I appreciate how you were able to tie together different data sources and walked ppl through the analysis!
I am guessing they used logistic regression because they could show the lead win probability as a function of emails opened. It's quite easy to do with logistic regression.
Re: Using machine learning to predict the leads that close
#7I worked previously at a company that was trying to do a predictive analytic, ML on top of Salesforce (to qualify and score leads, generate new promising leads, etc). The task was extremely difficult and from what I saw people were getting some marginal improvements from ML itself. Most companies at the end were interested in basic (but quite hard things to do right) - cleaning, dedupoing, enriching, generating more…
I hope though there will be an ML product that can do a decent improvement in this space. Even small improvement there brings significant ROI.
I spent years using a tool called Clari that applied analytics to Salesforce and Office (email) to predict deal activity. When it worked, it was really good.
But it had a fatal flaw: relying on Salesforce meant relying on the data that sales people input. And I quickly learned that sales people hate reporting tools, update them only under duress, and generally fill the database with crap.
Perhaps it's different when you are selling subscriptions over a digital channel, but for classic B2B feet on the street deals, ugh.
Re: Using machine learning to predict the leads that close
#8What should you do with this information though? Should the salespeople focus on the customers that are most likely to convert? Or should the salespeople give minimal attention to those, and focus most on the ones less likely, but not 0 probability, to convert.
I think the most important outputs of this are understanding the factors involved in conversion to tune business processes, not necessarily using the outputs of the model to target specific users.
Re: Using machine learning to predict the leads that close
#9Earlier quoted context omitted.
I hope though there will be an ML product that can do a decent improvement in this space. Even small improvement there brings significant ROI.
I spent years using a tool called Clari that applied analytics to Salesforce and Office (email) to predict deal activity. When it worked, it was really good. But it had a fatal flaw: relying on Salesforce meant relying on the data that sales people input. And I quickly learned that sales people hate reporting tools, update them only under duress, and generally fill the database with crap. Perhaps it's different when…
Thus spawning a whole new class of tools that add a more convenient interface on-top of salesforce.
Re: Using machine learning to predict the leads that close
#10Earlier quoted context omitted.
I spent years using a tool called Clari that applied analytics to Salesforce and Office (email) to predict deal activity. When it worked, it was really good. But it had a fatal flaw: relying on Salesforce meant relying on the data that sales people input. And I quickly learned that sales people hate reporting tools, update them only under duress, and generally fill the database with crap. Perhaps it's different when…
Thus spawning a whole new class of tools that add a more convenient interface on-top of salesforce.
Right, but garbage in, garbage out, whether you are feeding your CRM directly or via a shiny UI layer. No amount of ML can save you if the sales droid isnt filing data.