6 Ways Sales Data Analysis Can Help Your Business Strategy

As Villanova University found out, an increasing number of chief marketing officers are now beginning to allocate more money to market analytics. They report that the figures for an average American business are 6.5 percent. That’s how much of the marketing budget is being allocated to Sales Data Analysis! That’s not surprising given that it can help you answer crucial business strategy questions like, 

  • What should we do?
  • How should we do it?
  • How do we know if it’s working?

Not convinced yet? Then let us delve a bit into how Sales Data Analysis can help your business strategy:

Improving your Company’s Service Level Performance

Consider a business that delivers flowers. They get their orders off a network of florists. How can they improve the way they serve their customers? By using analytics, the company can predict customer behavior and meet the demands. Most of those are based on same-day delivery, which happens to be the Unique Selling Point (USP) for the business. Thus, they use analytics to understand the impact of traffic patterns. They also match it with the average time it takes their riders to deliver in major cities. In this way, they can meet the commitments they accept. When that isn’t possible, they won’t take the order. Of course, they do that after they propose a next day delivery. What makes all this possible? Sales Data Analysis!

Improving Value Propositions 

Sales Data Analysis-driven businesses can ensure they say the right thing, at the right time, and to the right customer. Developing value propositions can be difficult for most organizations. After all, that entails convincing each segment of their target audience that product A is right for them. In the end, most companies will choose a one-size-fits-all strategy. That’s why their tactics may work on one segment – or several more – but not all.

With analytics, companies can collect and cross-reference many data points. This gives them a chance to build highly-personalized value propositions. Using them on each customer segment means offering the latter a solution tailored to their specific needs.

Sales Data Analysis allows businesses to determine which out of all those segments are most valuable for them. That would prevent them from wasting money on the segments that likely won’t yield conversions. Harvard Business Review’s article mentions that this is also possible by assigning CLV (customer lifetime value) ratings to customers. Even if your organization doesn’t go that far, it can use Sales Data Analysis to prevent customer churn.

Improving Price Points

Setting the price for a new product can be challenging too. You’d want one that maximizes sales and revenue. Analyzing data can help companies test many different price points. They could determine when to upsell and when cross-selling will do the trick. They’d also find out the optimal price for each product — even for each segment of customers.

At times, raising prices will maximize revenues. In other instances, the opposite strategy may work. Since price increases can bring down the potential sales, you’d want data backing you up before you attempt it. The strategy works since the average size of each sale becomes larger.

Improving Pipeline Management

Sales Data Analysis also makes managing the pipeline better. Not knowing enough about the leads that fill up in the sales funnel limits their usefulness. How can your sales department cater to their needs if they don’t know them? 

Once you have segmented your prospects (lead qualification), you can prioritize them based on their profitability to the company (ranking). The next step is identifying the best product lines to offer them. Your sales department spends less time on leads that aren’t too likely to pan out. This can provide a boost to sales.

But there’s more that you can do with Sales Data Analysis. To do that, your team would need to run a historical analysis from your CRM system. This will allow the separation of the sales reps based on how they spent their time. Which part did they not spend enough time on? Could that be the reason behind a prospect loss? Highlight the area and then make up for it in the subsequent efforts. 

Finally, adjusting for pipeline trends and bottlenecks is also possible with data. How many calls does it take your average salesperson to close a deal? Do your reps know what is the minimum amount of calls they must make before considering a prospect as a loss?

For insights, you can apply this strategy to find out other factors behind prospect losses, such as customer engagement type and frequency, internal processes and capabilities, etc. 

Improving Identification of Business Opportunities

Sales Data Analysis increases efficiency in the sales process. Moreover, it can also help your business identify when new, hitherto-overlooked opportunities arise. Those include untapped customer segments. What does this mean for your company? It bases the potential for growth and profitability on intelligence. Thus, the possibility becomes endlessly expansive.

Additionally, with Sales Data Analysis, you can discern long-term trends as opposed to just short-term ones. Computer models based on data analytics can help your company see shifts in customer behavior. Through them, you can create a clear picture of what products you should highlight while updating others. 

Improving Multi-Channel Conversions

Sales Data Analysis is becoming more critical in recent years. It promotes multi-channel conversions too. For instance, it can provide you with information on how well your company is generating sales through mobile devices. Therefore, you’ll know if mobile shopping is something you should improve or not. The more compelling, positive experiences you can create through this channel, the more it will increase sales revenue.

Gone are the days when even professionals used gut feelings in place of business strategy. This is also not the era of, if I have Excel, that is all I’ll need. Now, data analysis is one important source that drives business strategy. If translated into a user-friendly format, even non-technical business users can interpret it. Moreover, it is highly affordable since most enterprise databases already store big data. Want to incorporate data analytics into your strategy for the benefit of your business? Call us, and we’ll guide you to the next step! 

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