Coaching is the most important factor impacting sales performance. Using analytics, sales leaders can improve coaching and gain transparent visibility into the performance of their reps. It is the most accurate way to identify the behaviors of top performers and coach to a standard, bridging the gap between your best and your average reps. No longer based on manually-entered, skewed data, sales analytics provided automatically by a sales acceleration tool are completely transparent, objective, and accurate.

Real-time analytics are a manger’s best asset. For example, it takes an average $30,000 and seven months to find and onboard a new salesperson. So, instead of enduring these costs, improve the performance of your current reps by coaching them towards success. Using analytics can even reduce training time by 30%. The successful sales manager will use this data to not only coach, but to establish best practice standards for both individual reps and their team as a whole.

Here are 3 ways sales analytics improve coaching:

1. Coach to a Standard by Applying the Right Metrics

When incorporating data into your coaching methods, start by finding a recipe for success. Sometimes reps make too many calls, and other times they aren’t making enough. Consider metrics ranging from the length of the conversation, number of calls made, and calls made to specific areas or time zones. Analyze speech analytics, look at conversion rates and average ramp-up time, and tag specific lines to share with your team.

To truly find coaching success with data, teach your reps X amount of info and see how they succeed. Then, introduce X amount of more info. This will allow you to measure KPIs of success based on the coaching you’ve given and see the influence of any increase or change in outreach, for good or for bad. It will be clear whether to continue, revert, or make new changes—all based on the numbers.

Additionally, A/B testing methods is an effective way to look at effectiveness based on the raw data, not opinion. Use the behavior of successful reps to show others what works, and how they can make specific adjustments to improve. Identify the behaviors that work for each individual rep and those that do not.

2. Apply the Insights Provided by Sales Data

With data, there is no need to argue my way is better—you just need to look at the numbers. Data provided by a sales acceleration tool makes coaching easier, as it is much easier to convince people they aren’t doing things right when you can simply show them.

However, managers need to also adopt a pattern of regular coaching with maintenance and repetition over time. According to Xerox, 87% of new skills are lost within a month of training. Keeping regular tabs on the performance of your team will ensure they continue to perform to a standard. The goal here is coaching to mastery; fine-tuning every aspect of a pitch, even the smallest details.

3. Coach by Listening

Data in the form of speech analytics and call recordings allows reps to hear what success sounds like and make the necessary adjustments. Patterns will begin to appear as reps start to identify what works best, and what does not.

By using data provided by call recordings, managers can share these recordings of their best reps to make good reps great. Since reps can see this data themselves, they can ask how they can improve, make their own adjustments to their approach, and adapt to the model of looking at what success sounds like for their peers.

Getting Results

The goal of coaching through analytics is not to reinvent the wheel, but to make the wheel that you have shinier. When done correctly, employee retention is higher because people are happier when they are performing better, and when they aren’t told what to do, because instead they are shown concrete proof of what works best. With analytics, managers also waste fewer resources on coaching, as the quality of approach results in lesser quantity due to increased, data-based effectiveness.

Learn more on how you can improve coaching at your organization through sales analytics.

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