Sellers that don’t have good data will struggle to repeat their success so we must recognize the importance of data in sales.    Kyle Morris operates a company called SifData which features an application that sits on Salesforce to help companies track job changes.     Defining data Sales reps are very intuitive. They understand things well and many people assume that anecdotes and data are the same. They assume that, because they closed a deal with a company similar to the one they are interacting with, that constitutes data. Because a tactic worked previously, they may assume that they can use that information as data moving forward.  In other words, they assume that if a tactic worked once, it’s solid and they should continue using it.  Kyle points out that the plural of anecdote isn’t data. We must stay objective and make decisions based upon actual information rather than sticking our finger to the wind to determine which way it’s blowing.  Data is  objective information about people, companies, or whatever your data set is that helps you make informed decisions. One of the easiest ways to identify the companies that could buy your product is by identifying the companies that have already bought your product. Figure out what’s common among them and then use that as a template to decide who to sell to in the future. If you’re selling to companies that are unique, you might find another market that also has that same commonality.   Some data will get you pretty far but you must be able to fill in the gaps that data doesn’t cover. Having anecdotes that prove your point isn’t the same as having data. #SalesData Data problems The two biggest problems common to data are that companies use data sources that are inconsistent and that they have too much data that isn’t actually valuable.  Consider Uber as an example. If you’re trying to sell to Uber, some sellers might consider it enterprise while others view it as mid-market since they only have a couple of thousand employees. LinkedIn might reflect that the company has 35,000 employees, including drivers. If companies aren’t careful about where they are choosing data, it can create confusion.  Be consistent about where you get data, even if it isn’t perfect, because you’ll at least be consistently wrong. Limit the number of resources you use to make classifications, especially for things like territories or number of employees or revenue.  Many CRMs have a full page of information that reps never use. It doesn’t add value and it actually becomes a burden to them. Approach this with the same mentality you use when designing your website: what’s above the fold is critically different than what’s below the fold.It’s impactful where things are placed, and if reps have a bunch of unnecessary information at the top of the form it burdens them.  If the reps don’t absolutely need it, then remove it. Streamline your process. Develop a discipline around reducing the amount of noise that your reps see based on the information they need. If the data won’t actually impact how they work through the sales process, it should be removed since it won’t actually move the needle.  Guesstimation Donald Miller says that if you confuse, you lose. We cannot confuse our reps. If we do, they’ll likely go back to what they’ve always done before, which is guesstimation.  Imagine driving a truck built in 1965 versus a fighter jet built in 2019. The truck likely haas a stick shift and like two buttons for the radio, so almost any person can use it to get from point A to point B. Put that same person in a fighter jet with a million buttons and they won’t understand how to move forward.  Sales reps must be able to execute and they shouldn’t be asked to fly a fighter jet if all they really need is a 1965 Chevy.  Additionally, more data points mean that some operator has to maintain those fields. You must make sure the information is accurate because inaccurate data will make your CRM less valuable. Again, if th