Here's how you can analyze and interpret sales data using logical reasoning.

I use to say that a good salesperson is the one that goes to the meeting well prepared. 90% is data and how you analyze. -Proactive offers -Solutions to problems (proactive if possible) -Savings for your customers This way you make the purchaser's wrking life easier, that is our job. See the bigger picture

Obtaining and assessing chronological sales data can be difficult if the organization doesn’t have underlying infrastructure. And yet, please make a good rapport with the data team to put your hands on at least the last three years of historical sales data in terms of revenue, unit price, accounts, sales date. SKU and a relevant sales taxonomy (new, recurring, renewal) etc.

Analyzing sales data will tell you which territory you shall focus on, what your target accounts are this fiscal year, what should be your sales motion, and how many salespeople you will need, and what sales activities shall be applied to attain your quota

If there’s a sudden spike of revenue without an apparent reason, it could flag an undermining market or sales behavior of long-term profitability. Starts from the metric analysis and completes with deep listening to your team, channel partner and customers.

If a client tells me my current annual sales is at $20 million and I want to be at $50 million this year, I simply break it down in the following manner: 1. Total proposals submitted 2. Total unique prospects spoken to 3. Total leads generated Thus, if the goal is to 2.5x sales, then I know we simply have to 2.5x pointer 3 (the lowest common denominator) = total leads generated, and the result will automatically take care of itself in most scenarios. Are there other approaches I apply to make them further efficient? ABSOLUTELY, but the above is the SIMPLEST to #assessperformance

Analyzing and interpreting sales data with logical reasoning can drive better decisions. Start by collecting accurate and relevant data from your CRM or sales platform. Break down the data into key metrics such as conversion rates, average deal size, and sales cycle length. Use logical reasoning to identify patterns and trends over time. Compare these metrics against your goals to assess performance. Utilize data visualization tools like charts and graphs to simplify complex data. Regularly review and adjust your strategies based on these insights. By applying logical reasoning to sales data, you'll make informed decisions to boost your sales performance.