Data Science in Sales

If you’ve ever seen the Brad Pitt movie Moneyball (or read the book it is based on), then you’re already familiar with how the principles of data science allows you to find opportunities that your competition might miss.

To get to the real heart of the matter as to why data science is so important in sales, let’s look at some areas where it can make an immediate impact on your business.

1. Improved Lead Generation

Every year, companies spend untold millions of dollars on efforts to generate new leads. New leads are vitally important to your sales success. After all, you can only up sell and cross sell so many items to your current customers.

Companies are already looking at their previous years’ market research to find the newest batch of potential customers, but this can be a time consuming and imprecise process.

Companies taking advantage of modern data science advances are using complex algorithms and machine learning to not only augment this research, but take it to another level.

For instance, it’s possible to view potential leads at a micro level – but modern artificial intelligence is able to take not only the historical customer data you have access to, but cross-reference it with external factors like the current news cycle, social media trends, and a multitude of other data points to give you a more focused view of your perfect customers.

Ultimately, the advantage data science provides here is an unprecedented level of insight.

Using data analysis allows you to not only find high quality leads you might have missed, but looking at how the leads you do have convert can give you insight into how your sales approach is working.

2. Puts the Right Rep with the Right Client

In a perfect world, all of your sales reps would be equally adept at closing deals no matter the customer.

In reality, we know this isn’t always the case. Data science is great for understanding the strengths (and weaknesses) of each member of your team, allowing you to put the perfect rep with each customer.

Beyond that, data analysis will also give you insights into how customers are responding to your sales methods. This can provide you with actionable insights that you can then apply to close more deals.

3. Increase Lifetime Customer Value

We briefly mentioned cross and up selling earlier in this piece. Did you know that data analysis can help us do this more effectively and efficiently?

One of the big benefits of using data science in your sales department is that it not only makes acquiring new leads easier, it can help you increase the average lifetime value of the customers you already have.

Think about that – rather than constantly chasing new business, you could instead focus your efforts in keeping people who’ve already said “yes” to your products in the fold. That’s a revenue increase that won’t cost you a small fortune.

Data science can help make this scenario a reality by helping you find the perfect opportunities to up sell and cross sell to customers.

Artificial intelligence is now able to analyze sales data and link items that people regularly purchase after buying other items. It’s how Amazon always knows the right thing to suggest to you in the site carousel.

Beyond that, data science can help you spot underserved segments of our customer base. When you find a customer segment you’re not reaching, it’s easier to build campaigns solely designed to target those customers.

It doesn’t stop there, either. A good data science program will look at your customer attrition rates and help you understand why customers aren’t offering you return business. Armed with this knowledge, it becomes easier to keep your current customers in the fold.

And finally, data science will not only show you how to keep the customers you have, but it can provide you ideas on how best to get them to buy again.

Beyond recommending products, a good sales enablement software solution will suggest supplementary materials likely to have the biggest impact on your clients. This eliminates a lot of guesswork.

These are just a few of the ways data science can help you take your sales to another level. The beauty of sales analytics is that you can gather data on almost anything – and today’s software can crunch those mountains of information and give you a roadmap to success.

6 Things You’ll Need to Succeed with Data Science

Now that you know some of the ways data science can benefit your business, let’s talk about five of the things you’ll need to focus on if you really want to succeed with a data analysis initiative.

1. Gathering your Data

It’s impossible to do data analysis without data, so the first step of a successful analytics program involves setting up systems to capture the information you’ll be analyzing.

A common mistake companies make at this stage is focusing solely on internal data. While the information you have on-hand from past customer interactions and historical sales figures is valuable, it provides only part of the picture.

To truly understand things, you’ll need to capture external data as well. Combined, the two elements will give you a more complete picture to analyze. The good news here is that modern software makes acquiring sales data easier than ever before.

2. Derive the Right Insights from your Data

The second step involves making sure you’re reaching the right conclusions based on the data you’ve gathered.

Many companies struggle here because they don’t have a team or person in the company who can help decipher all of this information. This is why it’s important to consider hiring a data analysis expert if you don’t already have one.

While a sales manager or VP can often look at the results and draw conclusions, to get the most out of data science, you’ll want someone who lives and breathes these numbers.

It’s worth the investment, too – having a qualified data expert on staff can pay for itself in a matter of months thanks to the newfound opportunities they’re likely to uncover.

3. Leverage Insights to Drive Actions

It’s great to understand the trends data science shows you, but if you’re not using those insights to drive action in your business, then what’s the point?

There are two basic approaches to driving action based on data analysis: human action or automated action.

In human action, we’ll take what we’ve learned from our data breakdown and put it into the hands of our sales reps so they can use it in the field or when interacting with customers.

Automated actions are things your sales AI can do – chatbots, emails, and things of that nature.

The key here is to take these things you’ve learned from your data analysis and make sure you’re actually putting it to use.

4. Measure Results

Data science can give you a great deal of valuable information, but it’s not an exact science. As such, there will be times when things don’t go quite as the numbers indicated.

This is why it’s important to measure your results at each step of the process. Machine learning is always evolving, and the more data and results you give your sales enablement software, the better it becomes at predicting results.

Don’t be afraid to look at the numbers and change course when things aren’t working.

5. Continue to Improve

Finally, in the last step, you’ll want to be sure you’re always improving.

Data science is an ever-evolving field thanks to advances in technology. What was cutting edge two years ago is often outdated today. Keep looking for new data sources, new technology, and new ways to make your data science team more efficient.

One way to beat the competition is to stay ahead of them. An often easier way is simply by being more organized, more efficient, and continually improving.

6. A Data Scientist Fluent in Sales

Adding an actual data scientist to your sales team can bring an added level of depth to your data analysis operations.

It can be tempting to go out and hire someone whose specialty is pure data science. After all, they understand data and analytics, so they’d be a perfect fit, right?

Not necessarily.

A data scientist might be great at analyzing data – but you’re often better served by finding someone who also understands your specific industry. This way, you’ll have someone who can not only analyze the numbers, but can put them in context in terms of how they relate to your specific vertical.

Someone who specializes solely in data analytics might lead to you getting an incomplete picture in their analysis. For example, if they don’t entirely understand your company’s specific sales cycle, running a regression analysis on your current cycle could yield unreliable information.

Beyond that, pure data scientists are often more interested in analytics – which is great, but part of implementing a data science program involves not only collecting that data, but using it to gain insights into how your business can be more efficient and profitable.

If your data science hire doesn’t understand your industry, you’re not likely to get really deep insights from their efforts.

Because of this, it’s often beneficial to look for someone who already understands your business. That can be a hire or an outside firm.

Whatever path you choose, just keep in mind that being great with analytics isn’t enough. The person needs to understand your company and market, too.

Final Thoughts

We used to say that data science was the way of the future, but that’s no longer true – data science is the way of now.

If you’re not using data analysis in your sales efforts, we can guarantee that you’re missing out on revenue opportunities, leads, and chances to improve your business. Even worse, your competition is almost assuredly already using these tools and either catching up with you in the market or passing you by.

Fortunately, data science is more accessible than ever. Reach out to use if you’d like to learn more about how these tools can improve your sales or to see what your options are in terms of software. We’d love to help you implement data analysis into your business.

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Accent Technologies is the first and only SaaS company to bring together Sales AI and Content Management in a true Revenue Enablement Platform. We provide both sales and marketing with better visibility into the performance of their teams. This drives revenue through intelligent recommendations for complex sales scenarios and provides the data for rich analytics that power better coaching, forecasting, and long-term customer support. Learn more about our solutions or request a live demo to see it in action.