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If you’re interested in increasing sales, utilizing the power of data could be the right move. Here are 5 ways to effectively leverage data for improving those sales. 

With the advent of digitalization and technology, Data has become a growing & pivotal aspect of the decision-making process. Through its quantitative reasoning, businesses can make smarter decisions.

Forbes Insights states data as the DNA behind compelling analytics & insights that assist modern organizations in identifying new products and improving operational efficiencies among others.

Moreover, a study performed by MIT Center (Digital Business) reveal businesses driven by data had:

  • 4% increased productivity
  • 6% higher profits compared to the average

This heavily implies the importance of leveraging data for drawing out business insights and converting those into profits. So, where do we start?

Well, there are several techniques/ways to leverage data for your business and today, we will explore some of the prominent ones. Here are 5 powerful ways you can effectively leverage data for increased sales.

1. Utilize Your Sales Data for Enhanced Operation

As they’re collected over time, sales data can crunch up numbers & key trends that allow you to uncover questions like – How much are we selling? What’s our monthly revenue? But beyond answering these and other pivotal questions, sales data can enable so much more.

It can allow your business to analyze & plan with enhanced accuracy. By utilizing a POS to track sales information, it can provide decision-makers the opportunity to go over historical data, move the right pieces and then checkmate!

Now, let’s illustrate an example. Suppose, your data projects show Sundays tend to consistently rank as your slowest day and it continues to do so for months. You can utilize this information and enhance your operation by making various adjustments.

You can try increasing marketing, limit hours, or even offer a promotion to garner more customers on Sundays. Bottom line is, this proves how data can provide a much clearer perspective on which actions to take if you want the numbers to rise.

2. Employ Traffic Analytics to Detect Unique Niche Market

Many online retailers have started opting for easily customizable and low-cost new business ideas (e.g. on-demand prints or personalized digital products). However, for such businesses to really take flight, their ad targeting & customer segmentation data has to be precise.

This is where proper data application can make a big difference. For broader traffic insights, leveraging analytical programs can help detect specific and profitable niches with an interest in your product.

You can utilize this information for your benefit and create customer profiles representing unique aspects of your audience. This, of course, should be backed by data of your current customers to avoid missing out on major segments.

This information highlights various demographically based unique niches (e.g. overseas buying groups or audiences interested in your product through specific keyword queries). This is how you can start detecting or identifying various niches that may already exist or could use better targeting.

3. Assessing Performance and Incentive Plans

In the presence of reliable data, sales managers can forecast sales for each rep and make comparisons between their current and past performances. When a sales rep scores a low performance, more time can be put on coaching & training by sales managers.

On another note, if a sales rep scores unusually high performance, the sales managers can acknowledge & reward them while also help train the team regarding their methods & tactics.

Additionally, by observing the data from your Customer Relationship Management or CRM, you can notice how reps use their time and identify the most impactful activities for closing deals & generating revenue.

Through collecting & analyzing the sales data, managers are able to become more effective & efficient at setting realistic goals, correcting performance issues, motivating team members, and incentivizing high performers.

4. Enhanced Engagement via Natural Language Processing

When brands manage customer engagement at the correct time, chances are, conversions and overall audience sentiment will increase, particularly in the case of social media as it can increase brand awareness.

However, the tricky part is knowing when & how to reach them. One way to get past this is, utilizing NLP or natural language processing tools to keep track of the timing. Through machine learning, NLP applies behavioral data against words that customers use.

This helps businesses determine their sentiment and figure out how to best respond, which is very crucial for conflict resolution. Today, customers are increasingly utilizing social media to voice out their experiences, so, businesses should be using NLP data to track these interactions and respond effectively.

Unfortunately, many brands fail to tackle this matter efficiently. According to a study from Sprout Social:

  • 89% of customers inquiries on social platforms remain ignored
  • 73% of customers notify businesses about their negative experience through social media
  • 30% of customers will ditch the brand for a competing brand if problems are left resolved

However, all is not lost. This same study also reveals how the tables are turned when brands move forward with positive customer interaction on social media and it can drastically improve overall revenue and customer sentiment.

5. Creating New Products & Services

A very interesting case of utilizing big data is launching new products & services through customer data analysis and several online & offline enterprises have adopted this to provide enhanced customer experience.

Analyzing big data enables enterprises to gain better customer understanding, which allows them to create new innovative products that can meet the viewpoint and needs of customers. For instance, a company that manufactures sports equipment created a type of complimentary service to optimize workout regime for athletes.

Businesses lose their operating revenue by about 20-35 % because of bad data. This shows how the use of data analytics can deliver great value for businesses worldwide and several enterprises have utilized it successfully in leveraging customer data.

This enabled the business enterprises to achieve better decision making, bring forward new offers, and not to forget, increased profits.

Final Thoughts

Thanks to our modern techniques of mining data, we’re able to amass a tremendous amount of customer data. However, utilizing it meaningfully is another thing and reaping its benefit is completely up to how we manage and observe those data.

To summarize, data is powerful enough for predicting consumer behavior and effectively improving sales when businesses are able to utilize it the right way.

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