Analyzing data isn’t new. Investopedia’s definition of the term states that “data analytics is the science of analyzing raw data to make conclusions about that information.”
While your first reaction might be to imagine algorithms and complicated number-crunching, successful businesses have been using data analytics for hundreds of years.
While today we can automate processes that tell us if a customer is likely to renew their contract based on different data points, back in the day business owners would do that analysis themselves. With that experience, they could learn which customer profile would be more likely to continue buying.
While that’s just one example of using data, the point stands. Analyzing the data available to a business with the goal of using it to steer the business towards success isn’t a modern invention.
However, modern technological advancements have resulted in businesses having access to a huge amount of data.
All these figures, statistics, and data points have the potential to be really useful in a business context, but being faced with all these numbers can be overwhelming and confusing if you don’t know what to do with them.
One McKinsey study has shown that fast-growing organizations use analytics more effectively than slow growers. That same study, however, highlights that many companies are struggling to use analytics effectively.
What does that mean? Using data analytics is a chance to get ahead of the competition.
The aim of this article is to provide some direction and ideas when it comes to applying data analytics in a way that can help you hit your best sales year yet as you look to stay ahead of the competition.
What can data tell us?
But first, let’s take a quick look at why data analytics is important for bringing in more revenue — what is there to actually learn from data?
- Sales data can predict bad-fit customers or highlight hidden opportunities.
- Analytics can help you maximize a customer’s lifetime value based on historical data.
- Certain data points can allow you to self-analyze your offerings and see where you can adapt.
- You can learn from other organizations’ data analyses as well — what do top performers do that you don’t?
Perhaps more importantly than any of that, once you overcome the fear and confusion that data can bring, you’ll find yourself with a renewed confidence that will help you hit your highest sales numbers yet.
How can data analytics be used to help boost sales?
Now that we understand what data can teach us, let’s dive into the ways that you can leverage data analytics to boost sales for your business.
1. Finding opportunities
It’s best to start at the beginning of the sales process — finding leads and finding prospects with the goal of turning them into actual customers. Where can data analytics come into play here?
One use of data analytics that is becoming increasingly popular is lead scoring.
Lead scoring is “a methodology used to determine the worthiness of potential customers by attaching values to them based on their behavior relating to their interest in products or services.”
While that is the technical definition of the methodology, the lead scoring process relies heavily on data analytics.
Algorithms can take existing historical data on prospects and current customers, combine it, and analyze it.
The result? You’ll get accurate predictions on prospects, which can be used to better understand a prospect and what needs to be done in order to convert that prospect into a customer. Lead scoring is an almost entirely data analytics-driven process that you can build your sales strategy around, resulting in more revenue.
These algorithms can be used to predict which leads are most likely to convert, so you can target them.
The possibilities that data analytics bring to lead generation don’t stop there, however. Companies are using artificial intelligence (AI) in their technology stacks to leverage this data further.
Examples include sales enablement departments that use AI-driven content management systems that surface the best message for a salesperson to deliver to a prospect.
Meanwhile, some organizations even automate early lead-generation activities using AI.
While we can clearly see the benefits that processes like lead scoring can bring, it’s important to remember that none of it is possible without in-depth data analysis, driven by modern advancements in algorithms and AI.
2. Getting the most out of current customers
Data analytics doesn’t just help you sell more effectively to potential customers. It can also change how you upsell and cross-sell to your existing customers.
By doing a deeper analysis of the data from your current clientele, you can identify patterns and glean new information. With this new information, you can start to look at opportunities within your current customer base.
How do you get these new insights? Start by analyzing and segmenting your customers into groups. These groups should be based on shared attributes, including average spend, location, and more.
Once you have these segments analyzed, you can start to understand which groups are more likely to be receptive to upselling and cross-selling, and when.
With time, you’ll be able to start maximizing a customer’s value. A sale doesn’t have to mean the end of a customer’s journey with you — there are plenty of opportunities to continue that relationship.
If you’ve conducted (and continue to conduct) up-to-date data analysis, you’ll discover upsell and cross-sell opportunities that you otherwise wouldn’t have seen.
An important factor to remember is that this has to be a continuous process — analyze, apply what you’ve learned, measure the results, and then apply your learnings. If you do it right, you’ll start seeing customers stick around for longer, and spending more while they do.
That’s one surefire way to increase your sales numbers, and all it takes is a bit of data analytics.
3. Improving price points
Analyzing data can provide new insights into the price of your products and services, and these insights can lead to increased revenue.
You can compare with your competitors and the market at large and use that information to adjust your pricing. You may find out that different prices are more effective, not just based on which product you’re selling, but also on which group of customers you’re targeting.
One way to boost profits for your business would be to raise prices. Although fewer customers may be willing to buy at higher prices, the sales that you do make will turn higher profits, leading to higher revenue overall.
This may help you hit bigger numbers than ever before, but you can’t do it through guesswork. Careful analysis of data will allow you to make informed decisions on your prices.
4. Analyzing your own offerings
Through data analysis, you can achieve a true bird’s eye view of your company’s offerings. Which of your products or services sell well? Which are less popular? Is anything underperforming compared to your expectations?
Rather than using guesswork, analyze the actual data you have on hand. It’s a great way to learn more information about your business, your customers, and the wider market as well.
If you notice that a product’s popularity has been steadily declining, examine why. Has the product’s quality declines, or is a new competitor sweeping the market?
If a product is performing better than expected, that’s great news! But it’s still important to try and understand why this is happening so that you can adjust your sales strategy accordingly.
Data analysis makes this process consistent and reliable.
While this may not directly increase your revenue like some of the other points on this list, it does provide you with springboard opportunities — it allows for you to change and adapt your strategy based on the new information.
5. Enhancing the customer experience
As with the previous point, this isn’t all about bringing in more money and more customers. It’s about creating a culture of positive customer experiences in your company, which in the long run increases retention, loyalty, and upsell and cross-sell opportunities.
Data analytics provides you with opportunities to spot and reconnect with customers that you’ve noticed slipping away. Alongside proper data hygiene practices, it allows you to provide customers with personalized interactions which are of a higher quality, meaning they’ll be more likely to stick around.
Do you have a customer who’s been buying X amount of a product from you for 18 months and has suddenly stopped? Analyzing the data can alert you to this, meaning that you can call them and have a meaningful, valuable conversation.
The data can also flag situations where a customer is likely to drop off. If the amount they are spending is steadily decreasing, that can be a prompt to contact them and get them back on board.
If you’re dealing with a high volume of customers, these things can be nearly impossible to spot without analyzing the data on a regular basis. The rise of sales and revenue enablement within organizations has put customer experience at the forefront with great results. It’s clear that creating a good customer experience provides a platform for all your other processes.
Do this, keep a steady customer base, and you’ll see your reputation grow — which will inevitably lead to better sales numbers.
6. Learning from the competition
Data analytics doesn’t just apply to you and what you know about your own organization. There’s plenty of data to be found on your competitors, and that’s a prime opportunity to improve business and sales figures.
Competitive analyses can be conducted in a variety of ways, and can be based on quantitative or qualitative data.
Whether you’re basing the competitive intelligence data you’re gathering on surveys with customers and feedback from around the web, or if you’re using figures from SEO analysis, the end goal is the same: to look at your competitors and see where they are performing well, and how you can react to that.
If you’re neck-and-neck with a competitor, and can learn from what they’re doing well (or from their mistakes), you’ll have the chance to overtake them by implementing those learnings into your sales strategy.
For example, something as seemingly simple as taking advantage of color psychology with your marketing can make a huge difference. There's a reason why brands such as Google, Starbucks, and Coca-Cola have brands that are easily identified by their color palette. If you see that your competitor has a strong brand, but yours is still undeveloped, this could be a key area to focus on.
A better sales and marketing strategy will ultimately lead to more sales and a better sales year. There’s no reason not to monitor your competitors if that’s the case!
As this article wraps up, it’s important to note two things.
Firstly, data analytics is a broad area, and it encompasses much more than what was covered in this article. Data comes in all shapes and sizes, and can be analyzed in a lot of different ways.
However, the points covered above are a good starting point to consider when you’re beginning to incorporate data analytics into your processes.
Secondly, data analytics isn’t a silver bullet that will immediately increase your sales numbers by 300%. But it’s important to remember that analyzing data and instilling a culture of data analytics in your team can help you succeed, and many top organizations are taking the path towards becoming more data-driven in their decision-making.
Not using data analytics does put you at risk of being left behind.
All in all, data is more important than ever in a business environment, and it has so many uses and applications that using it in even just one context could really push your sales numbers higher than before.
Whether you’re using data to segment your existing customers to find upsell and cross-sell opportunities, to analyze your lead lists to find the best prospects, or examining what you can learn from your rivals, there are opportunities aplenty to use data analytics to help you hit your best sales year yet in 2022.