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5 Powerful Ways Data-Driven Decision Making Can Help Your SME

Data has become the lifeblood of customer conversion – its analysis can help companies make intelligent decisions, including how to market their products and services, who they should target, which channels or payment methods to use and how to measure success.

This is especially true for small and medium enterprises (SMEs). For SMEs, big data doesn’t just mean more information about their customers; it means having the correct information at the right time.

According to McKinsey, data-driven organisations are 23 times more likely to acquire customers, six times as likely to retain customers and 19 times more likely to be profitable – this leads to happy customers that remain loyal to your brand and return over and over again.

Why data-driven decisions are so important
The rise of the data-driven leader is an exciting shift for organisations. As our information sources become more numerous, it’s essential to make data-driven preparations for wiser decisions that could lead to more efficient processes and higher customer satisfaction.

As a small business owner, it simply isn’t enough to follow your gut instinct when it comes to big decisions. Building and nurturing data-driven outcomes in your SMEs growth strategy is a critical component of success.

Often referred to as information-based decision-making, this approach helps your business bring together historical information to analyse trends and plan for the future based on what has worked in the past – rather than make decisions relying on gut feelings, opinion or experience.

How Data can help your business

1. Targetting customers intelligently
If you’re a small or medium business owner, you need to pay attention to what your client base looks like. That means understanding your customers — where they shop, what they buy, how much they spend, and who your most profitable customers are. This information is particularly useful in determining how you market to your clients. At each stage of the customer journey, be aware of what data should be collected to help you make marketing decisions specifically tailored to that stage.

2. Understanding your customer journey
You can also use data to understand better which marketing channels perform best. For every customer who contacts you, finding actionable insights can reveal a lot of opportunities for improvement. Did your clients opt for a free trial before engaging with you? How many minutes did they spend on your website before making a purchase? How did they land on your website in the first place? All of this data is actionable for your business.

3. Diving into spending behaviours
Another essential component is understanding how your customers spend money and what drives them to buy online or in-store. Using a platform that offers insights from all your payments data, whether it’s coming from a POS, your website or a mobile source – will help your business identify patterns in spending behaviour. These can be used to trigger real-time communications, relevant content and targeted offers at critical moments in the customer journey.

4. Staying on top of trends
Social media presence is growing at an exponential rate – in 2020 alone, during every minute of each day, Instagram users posted over 300K stories, WhatsApp users shared over 41M messages, and Twitter gained over 319 users. Data can help small and medium businesses measure the effectiveness of their social media efforts, as well as track trends that might impact the business in the future.

Almost all of the customers’ digital behaviour is recorded. However, for many companies, this data sits in dashboards and databases, never to be used. An intelligent decision is to use this information to drive business decisions around marketing efforts or enable faster social payments, for example.

5. Empowering your workforce
To fully embrace a culture of making data-driven decisions, businesses need to give their employees comprehensive training and access to their analytics tools and data. When employees are invited into the analytic process, they are empowered to understand customer journeys better and suggest process improvements. Businesses that enable employee access to internal and external data are expected to double the value of the data collected along with the analytics investment.

Conclusion

Big data has taken over, and data-driven decisions are transforming how companies do business. Data science teams are becoming a usual presence in both large and small companies – this shows the importance of this new commodity and its real potential to make your decisions better.

To compete with big brands, SMEs need to adopt a data-driven approach to their marketing. Only then can they keep up with the competition and take their business to the next level.

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