Predictive Analytics: The power of anticipating scenarios

When to launch a specific product? How much is the consumer willing to pay for a particular product or service? How will the market respond in the next six months? What power do data have to enable us to anticipate scenarios and be more efficient?

Predictive analytics answers these questions, using historical data to anticipate scenarios, behaviours and opportunities. Thus, organisations can align how they interact with their customers, increase the efficiency of their processes and create more targeted strategies.

What is predictive analytics?

Predictive analytics uses statistical techniques, historical data and Machine Learning algorithms to identify patterns and predict future events or outcomes.

A management model based on predictive analytics makes it possible to reduce business risks since it is possible to anticipate trends, learn about new consumer habits and predict behaviour using Data Analytics, Artificial Intelligence and Machine Learning techniques.

Agility is crucial when it comes to making decisions and doing business. Today, more ample room is needed for decisions based on intuition or long hours analysing data compiled in Excel sheets. By having innovative technological solutions at your disposal, you can respond more quickly and assertively, whether to the emergence of new players in the market, consumer trends or changes in the sector.

Predictive analytics can be used in several departments in your organisation; everyone gets countless benefits from marketing to finance.

With the most disruptive technological solutions, you can get a more realistic view of what lies ahead for good results. You can make better decisions and get ahead of the competition by mapping patterns.

Predictive Analytics and Marketing

Due to the enormous volume of information available in your organisation, gathering data about your customers and analysing their behaviour and buying habits can be time-consuming. If it is not done correctly, we may be basing ourselves on limited information, leading us to make wrong decisions and thus interfering with the company’s profitability.

Knowing your customers is critical in developing and implementing an effective and assertive marketing and sales strategy. And this is where technology has a huge impact.

According to patterns, purchase history, preferences and behaviours, it is possible to predict consumer behaviour: what the consumer wants, how and where thus allowing scenarios to be anticipated, new opportunities to be discovered and more segmented campaigns to be created and developed with the confidence that the desired target will be reached. This analysis has an enormous wealth of information, from the perception of the brand, product or the level of customer satisfaction, for example.

Through predictive analytics, it is possible to understand the consumer profile, from how he interacts on the Internet to his buying patterns, which makes it possible to design a unique and personalised strategy, boosting an increase in the ROI of marketing and sales campaigns.

Consumers are increasingly looking for services and/or products to be more personalised and connected to emotion, offering benefits and distinction at a competitive price. With the efficient use of Data Analytics and Artificial Intelligence solutions, your organisation can provide a unique and attractive service and/or product according to consumers’ expectations, interests and needs, which opens the way to many business opportunities and allows you to bring more intelligence to your business.

Predictive Analytics and customer churn

Retaining customers is less expensive than acquiring new ones, and according to the Harvard Business Review: “Getting a new customer costs between 5 and 25 times more than retaining an existing customer”.

By using predictive models, it is possible to identify customers at risk of leaving and the reasons that increase that risk, allowing the organisation to respond promptly and make data-driven decisions to not only retain them but also increase the retention rate.

By identifying the reasons behind customer churn, the company can improve the customer experience and customer satisfaction.

Predicting customer churn thus brings numerous benefits, in addition to those mentioned, allowing for better decision-making, increased competitiveness and improved customer loyalty.

Benefits of Predictive Analytics for the business:

  1. Better Decision Making – Predictive analytics helps companies make better decisions by providing insights into future trends, customer behaviour, and market conditions.
  2. Greater Efficiency – Optimises operations and processes, reducing costs, errors, and greater efficiency.
  3. Customer Experience- Improve the customer experience by personalising products and services and targeting marketing campaigns. Respond effectively and make the customer experience more positive and efficient.
  4. Risk management – Predictive analytics can help businesses identify and mitigate risks such as fraud or financial losses.
  5. Marketing strategies – Understand the market and the customer with a 360º view, align strategy and create new business opportunities.

Predictive analytics can help businesses make better decisions, improve efficiency, and increase revenue. It is becoming increasingly popular with the growth of great Machine Learning technologies, making it more accessible to businesses of all sizes.

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