How are companies finding a greater use for analytics and data sciences?

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In an era when roughly two-thirds of companies have more data than they can analyze, sifting through big data has become a challenge that businesses now face. At the same time, customers are aware of the greater stores of data that businesses possess and what they know about them.

Subsequently, we’re beginning to see a trend where customers expect more of companies – including a more personalized service – because “they know me.”

As such, for businesses both large and small, they’re competing with their peers and to satisfy existing customers at the same time. This is why analytics and data science has become such a hot button topic driving its increased usage.

Here are some thoughts on how companies are making use of data and using analytics to overcome this data hurdle.

Customers’ Wants and Needs: The Answer?

What do your customers want and expect from your business?

It’s often difficult to answer that question. Surely, every customer wants different things. Well, yes and no.

Ultimately, customers do fall into different groups with similar interests and/or requirements.

For instance, Amazon.com found that people who liked several of the same TV series were likely to enjoy certain other ones. It was able to recommend them and increase the likelihood of extra sales and more satisfied customers. A win-win.

Companies are looking to figure out algorithms to search their data and find the nuggets of useful information leading to actionable insights. The information is in there – they just have to locate it.

Product Improvements & New Features Based on Feedback

Data analytics is also one of the most in-demand skills right now – click here to learn more.

One of the reasons is because it assists companies with product improvements and adding new features.

Customers’ Feedback Leads to Product Improvements

Sometimes product designers are married to the initial concept and find it difficult to think outside the box. Rarely is the first version of the final one.

Companies can use customer feedback to reevaluate what they have, ways to fix reported problems, and more. When they only tap fresh thinking from employees, they risk competitors innovating faster and better than them.

New Features Also Originate from Customers Too

Both customer suggestions and their frustrations provide fodder for designers to reimagine the product to create a whole new design.

Alternatively, when the data indicates that a certain feature is finickity and problematic for a significant percentage of users, it’s worth redesigning it to remove this sticking point.

Was a Product Just Bad or Badly Marketed?

When a product in the range doesn’t sell well, what’s the root cause?

  • Need? – It could be that it’s just a product that didn’t address a real need.
  • Bad Design? – It may be a badly made or poorly designed product that doesn’t work as intended. Customer feedback should confirm this.
  • Marketed to the Wrong Market? – The product was fine, but it wasn’t marketed at the correct target audience or demographic. It was aimed at Generation X but it’s the Millennials that liked it – sadly, the product packaging and features weren’t intended for them, so it fell a little flat.

Only by using data analytics to burrow through the information is it possible to know for sure which reasons are valid (and those to completely discard).

Reducing the Risk Factors

Creating a new product is inherently risky. And expensive.

Companies can ill-afford a major misstep and it risks a PR nightmare should it happen, which may have a deleterious effect on the sales of other products under the same brand.

Customers are often vocal about products that they’d wish were available, but they cannot find them in the marketplace. Often, they mention this in emails, feedback forms, surveys, and other points of contact. It’s up to data analytics to find and extract these bits of data together to create a cohesive view of the potential for a new product.

By listening better to customers, businesses steal a march on their peers by offering what they want rather than having to say, “Sorry, we don’t offer something like that yet.” Also, customers notice when the business starts to develop new products that were seemingly exactly what they wanted if they’d only thought to ask for it.

In Conclusion

Originally, companies were forced to operate on faith about what customers wanted. Initial sparks of an idea were developed into a new product. However, listening to customers became paramount because other competitors spotted a new opportunity would enter the market too.

In the modern age, this early beginning to product development and redevelopment has changed forever through the use of data analytics. It’s meant that businesses that fail to listen will inevitably fall behind. And this usually spells disaster for their long-term viability.

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