How Will Data Science Assist Mid-Sized Businesses In 2023?

The power of data benefits more than just industry behemoths. Emerging businesses can also benefit from insights and use them to fuel their decision-making processes. While progress may be slower due to scale, implementing a data-driven strategy in business can help accelerate growth and transform a small or mid-sized organisation both internally and externally.

If you want to learn more about how small businesses can use data, watch our dedicated video below, then keep scrolling to learn how a mid-sized company can promote business growth through data-driven strategies. In this article, we’ll look at some of the challenges that small and medium-sized businesses face, as well as some data-driven business solutions, through the lens of a fictional audiobook platform.

Growing A Small Business Into A Medium-Sized One Presents Several Challenges:

– Additional organisational structure layers

– Most employees have no direct access to leadership

-Require an increase in revenue

-Direct competition from major industry players

So, how can emerging businesses deal with these issues? Using data-driven decision-making is one of the best ways to address these issues. Clear KPIs and business goals centred on achieving them, for example, provide everyone in the organisation with a sense of purpose and a common goal. Furthermore, data analysis may provide insights into how to deal with competition.

In general, it is not advisable for a mid-sized company to compete with much larger competitors. Instead, it would be smarter to take advantage of customer data and try to define defensible portions of the market.

How Should A Mid-Sized Business Implement A Data-Driven Business Strategy?

Why is data so critical to business success? Consider a practical example that demonstrates how data-driven decision-making can be critical for a mid-sized business. We’ll look at a fictional organization’s business model, the strategies they used, and the outcomes.

• Business Plan

Audimax, a digital platform for on-demand audiobook consumption, hired an additional 150 employees following the completion of its Series B financing. So far, the company has been able to grow and gain customers by offering niche book titles in their catalogue that other platforms did not. Moreover, they also relied extensively on the quality of production. The voiceover actors hired to read audiobooks were carefully chosen and given extensive feedback on how to provide an excellent experience for Audimax’s listeners.

Management’s initial strategy was to publish audiobooks in various genres in order to reach a larger audience. Their idea was to publish niche titles that customers would want to listen to in order to entice them to subscribe to the service. a few other people in the world, in this case, the world’s population.

Audimax’s model had changed several months after the Series B round, though not in the way that the company’s leadership had hoped. One of the firm’s key business goals was to significantly expand the content library in order to compete with larger audiobook players. The newly hired voiceover and production talent, on the other hand, struggled to meet previous standards. According to customer feedback, some of the new titles were not as good as previous interpretations.

• Business Difficulties

At the same time, recurring revenue reached a plateau due to increased customer churn. And, to some extent, it was due to price competition from one of the world’s largest digital retailers, which had recently launched an audiobook platform as well. The mid-sized business couldn’t compete with the retail behemoth’s scale, existing customer list, and ability to market to specific clients.

However, their decision-making was on the right path. Audimax’s business expansion had piqued the interest of their competitor. As a result, the retailer launched a price war with promotion as ammo (selling subscriptions at 50% off), encompassing some of the most popular Audimax titles.

• Business Data Science

The good news is that a mid-sized business has much less bureaucracy. When Audimax’s management realised there was a problem, they began working on solutions much faster than a large corporation would.

As a result, the company used some of the funds raised in the Series B financing to form a data team. Several full-time data analysts and data scientists joined the company. They set out to better understand their customers and address Audimax’s churn issue.

After some thought, the data team arrived at the following conclusions:

-Newly released titles received significantly lower ratings than older titles.

-Some of Audimax’s new titles kept customers listening for much shorter periods of time.

-The company had titles in their catalogue that almost no one was listening to.

These insights revealed a problem with the operation. As previously stated, the production quality had deteriorated, and the goal of expanding the content library across multiple genres had not yielded the desired results.

Business Solutions Based On Data

Management decided on the following corrective actions to avoid a downward spiral:

-Practicing quality control

-Using machine learning techniques

-Identifying the target audience

First, a few data analysts were tasked with creating a dashboard that would allow them to track audiobook performance by genre and individual title. As a result, production teams could receive real-time feedback on the quality of their work, identify their weak points, and work to improve them. Furthermore, this aided decision-making when it came to hiring voiceover talent.

Another significant change in Audimax’s business strategy was the incorporation of a recommender system within the platform. The data team created a machine learning algorithm that would suggest titles based on previous customers with similar interests.

Third, the data scientists developed a clustering model that clearly demonstrated an issue within a specific group with significantly higher churn rates: younger users, presumably students, consumed audiobooks only during the summer. Simultaneously, Audimax’s management discovered that marketing had been investing their advertising budget to target the 18 to 22 age group, which resulted in the addition of more customers with a higher churn rate to the overall customer mix. Fortunately, all of that was simple to correct. The company focused on users between the ages of 25 and 34, who were slightly more expensive to convert into paying customers but had much lower churn rates.

All of these data-driven improvements enabled Audimax to continue growing its business in order to attract additional funding through Series C and D financing.

How Data Science Can Assist Mid-Sized Businesses: Next Steps

The practical example we provided demonstrates why data is important in business by identifying problem areas and providing actionable solutions. Investing in quality data talent or upskilling internal team members can truly transform decision-making strategy.