Information is valuable. Whether that information comes in the form of business intelligence, data analytics, or personal information, it can make all the difference when it comes to making informed decisions about your business and your life. That’s why the world of data analytics has grown into such an important field, and why companies around the world are starting to make investments in this area. Whether you’re looking to provide information for your own company or to bring valuable information to others, these five tips will help you start working with data analytics today!
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| How can data analytics |
Results of the analysis
We identified at least five key data points that led to the increase in sales. We started by analyzing our social media activity. We noticed that every time we had an Instagram post, our number of likes went up, but when we had a Twitter post, our number of followers did not increase. This made us realize that not everyone who sees the company's posts would be interested in following them on social media. The next day, we spent over an hour reposting all of the images from our recent Instagram posts to Twitter and received a surge in new followers almost immediately afterwards.
Analysis step 1 - Review of baseline data
There are four steps to analyzing data. The first step is to review the baseline data for your company. While different companies will have different metrics for success, there are some general metrics that are standard and can provide insight into how the company may be performing. Metrics such as turnover rate, customer satisfaction rates, and market share can tell you a lot about what is happening in your industry and how your company is positioned relative to the competition.
Based on industry averages, your turnover rate should be anywhere from 15 to 30 percent. If you’re higher than that number, it means that you are losing more workers than expected—and those people are taking their skill sets and experience with them. Either your company has a reputation for being a bad place to work, or it simply is not able to provide employees with opportunities for growth or advancement.
Analysis step 2 - Forecasting and results
So the second step is a forecast of the results from your decision. Did you plan to raise your prices? If so, how much higher? Did you want to reduce marketing expenses? If so, by how much? What about the price elasticity of demand for your product or service? This will take some detailed analysis but can be accomplished in various ways such as through secondary research, surveys, or reading through industry reports. Hopefully we will now have a clear picture of whether our new strategy had any effect on sales at all. If it has succeeded we might have to refine our next steps with revised data in mind or adjust our strategy again if not successful.
Analysis step 3 - New approach based on sales cycle stages
The first step is to differentiate by looking at each phase of the sales cycle (see below). Next, for each stage we analyze past trends and behaviors to identify opportunities for improvement. Finally, we make a plan by establishing clear goals and assigning a target date for their completion.
I. Market & Industry Analysis - Get up-to-date data about the market size, global economic conditions, competitors and more
II. Product & Customer Analysis - See how customers use products or services currently and what they want in the future
III. Lead Generation & Communication Analysis - Understand where potential leads are coming from (i.e., local vs national) and evaluate how communication campaigns are performing
Analysis step 4 - Comparison of forecast vs. actual data
It is now time to analyze the sales data and assess how well forecasts correlate with actuals. Remember, if the error of a forecast equals zero, it means that the forecast was accurate. But how accurate were the forecasts made in this case? The forecasted values, shown as blue bars in Figure 2, were plotted against the actual values, shown as green bars in Figure 2.
It can be seen that sales volumes were forecasted very accurately in all months, while they tend to under-forecast in June and over-forecast in December. This is shown by comparing actual values against their respective 95% confidence intervals. For example, if a 95% confidence interval for sales volume was [100,120], then if sales volume in that month turned out to be 100 or less or 120 or more, we would have reason to question its accuracy.
Conclusion and summary
Today, we've shown you how one company was able to use data analytics to improve their sales and business in just six months. Data analytics is a way for companies to better understand who their customers are and what they want. Data can then be collected, processed, and analyzed to help companies make strategic decisions and predictions on how the market will evolve. This case study has shown that with a lot of hard work, commitment, and creativity, one company was able to make big strides in increasing its sales.
If you're still not sure whether to invest in data analytics, consider what your competitors are doing. Today, many companies are already using data analytics to make their business better and more efficient. By investing in data analytics, you'll be able to catch up with these competitors, and even surpass them. It's one way that an up-and-coming company can gain an edge over its competition while also gaining valuable insight into its customers' needs and wants. So don't wait any longer—use today's information to get started on your own data analytics project!
