Geoffrey Moore, a well-known business advisor and author, rightly said, “Without data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway,” back in 2012 — but his words are making more sense today in 2022 than ever before.
Mining sales data is the gateway to preparing a roadmap for success for any business. It allows for converting raw data into informed data that can help identify sales trends, understand customer behaviour and measure sales performance.
Such a thorough analysis takes a business's operations to a whole another level by:
- Predicting valuable customer insights
- Building accurate sales forecasts
- Developing smarter sales campaigns
- Streamlining sales operations
- Increasing ROI
To do this, however, one must have an eagle eye to scan the sales landscape and the expertise to decipher data. Let’s take a closer look at some ways you can do it too.
Five Strategies To Effectively Analyse Sales Trends And Performance
While sales data can be of substantial value, deciphering it often gets overwhelming for even the most experienced sales teams. Luckily, with the right tactical approach, such an analysis doesn’t have to be daunting.
Here are a few unique ways to extract valuable sales trends and insights from the pool of data you collect:
1. Conduct an overall sales performance analysis
Sales performance analysis helps gauge the effectiveness of the chalked-out sales process. In addition, a thorough analysis can come in handy for fixing vulnerabilities in the sales process.
You can conduct this analysis by reviewing the following key performance indicators (KPIs):
- Studying sales operations metrics such as average time taken for lead to respond, length of the sales cycle and your average cost per lead.
- Review engagement by digging deep into metrics like bounce rates, page views, signups, likes, etc.
- Studying analytics metrics such as the growth rate, sales by each product, average value of sales per date, etc.
- Learning about performance metrics like average deal size, total revenue made for the year, pipeline value, etc.
Such an analysis can help managers draw an effective sales strategy in the future. In addition, he can further work on the gaps based on his learnings concerning the best strategies for working for the team, best-selling products, well-performing candidates, etc.
2. Drill down data based on factorisation
Another great way to study sales trends is by zooming in on a granular view by considering factors relevant to your business. For example, if you deal in seasonal products or services, you can study your sales data based on time frames.
Sales of such products inflate during the seasonal months and don’t fluctuate much over the rest of the year. Thus, a year-over-year sales study can help you compare your current year’s sales with last year’s to draw your progress.
Using multiple sales channels could be another factor you can consider for studying your data. For example, you can split your sales based on distribution channels such as Amazon, eBay, etc., and make strategic decisions about where you should invest your crucial time and energy based on the results they’re providing you instead of being equally invested in all the channels.
3. Determine the cannibalisation rate
Often businesses fear how a new product launch is going to have an impact on the customers and the business itself. While a successful new launch can bring in a good response, there is also a fear of overshadowing existing product demand.
As a result, it can be troublesome for businesses that want to focus on the existing products.
The cannibalisation rate thereby helps determine how a new product's profitability impacts existing products' profitability. It can be estimated by dividing the sales loss of an existing product by sales of the new product.
Understanding how customers perceive freshly released items compared to older or discontinued products can help businesses determine better decisions and approaches to update, improve, or renew older product versions.
4. Conduct a diagnostic sales analysis
Just studying sales metrics alone does not suffice. Results come in when you take a step further by targeting the real reasons behind the sales metrics.
For example, you launched an app and recognised a good increase in the number of your app downloads. However, in your sales reports, you notice that your customer retention was poor after a few months. The disconnect could be due to poor client service, complex interface design, insufficient features, or other reasons.
Therefore, diagnostic sales analysis will help you delve into the possibilities for this kind of disconnect. It’ll help you understand how two or more variables correlate — eventually helping you develop strategies to improve your processes in place.
5. Analyse customer feedback
The real gold lies here. Gathering customer feedback is one of the best ways for:
- Getting a better understanding of your business’ progress
- Understanding customer needs
- Shaping product roadmaps
- Increasing the likelihood of upselling and cross-selling to the customer.
Some ways to collect customer feedback are through chats, surveys, social media, etc. Once the data is collated, you can categorise feedback based on the types and introduce changes or improvements based on your business’ priorities.
Embrace a Data-Driven Business Culture
Sales data analysis can be a powerful tool for setting the foundation of a sales cycle that performs at its peak. Businesses that aim to refine their processes by taking advantage of such approaches can significantly improve their return on sales activities.
You can also deploy Customer Relationship Management (CRM) tools to ease the sales data analysis further. They help prepare sales analysis reports in a fraction of seconds — to help you sell smarter, monitor progress toward goals and quickly identify problems.
You can join Juno school to get yourself more well-versed with hands-on experience with tools such as CRMs and other sales methodologies. To learn more, visit our website today.
