How consumer analytics is changing business models

Consumer analytics is changing and improving business models, which are essentially the design of business operations covering different areas, like financing methods, customer interaction and product/service development. It attempts to answer questions like “What are we providing?” and “How do we do it properly?”. With the granular insights from consumer analytics, there is a lot of potential for organisations to fundamentally transform their business model to increase profitability, reduce costs and lower chances of failure. In this blog, I am going to explain how data analytics transforms business models and how that affects the customer-organisation dynamic.

Organisations make better, smarter decisions

Organisations are beset with challenges from intense competition to government regulation. Businesses constantly have to meet all regulations without breaking the law, while still making a profit in a competitive market. This is where we find the value of consumer analytics. Data analytics paves the way for techniques that were previously difficult to accomplish, like dynamic pricing. Setting a price that covers (fixed and variable) costs while still tempting the consumer is a trying task, but analytics can analyse the demand curves for different consumers to help organisations set the right price for each customer.

Furthermore, inventory managed more intelligently can minimise stock management costs. Consumer analytics can analyse and predict consumer demand, allowing organisations to smartly manage their inventory to minimise costs and be more responsive to consumer usage. Organisations can make smarter decisions on current stock levels, when to stock and the total quantity to stock.

Analytics delivers a deeper understanding of consumers

If there is one challenge most B2C companies have, it is staying relevant to their customers. Whether it is a lack of new products or friction in the customer journey, organisations often have difficulty building a strong relationship with their customers. However, consumer analytics goes a long way in addressing this problem by giving a deeper and better perspective on how customers think and behave. Sentiment analysis allows organisations to analyse customer feedback provided on different mediums, like customer calls to decide if the overall sentiment is negative and positive. A deeper understanding of consumers helps companies ignore the tone of the vocal minority and make intelligent adjustments to products and services where needed.

Another important aspect of understanding consumers is the customer journey. Customers go through several steps before deciding to make a purchase, if there is friction in the process, then the customer will leave without purchasing anything. Understanding the customer journey is crucial for business success. Fortunately, consumer analytics is one of the best ways to better understand the journey, highlight flaws and fix them.

Consumer analytics can study touchpoints in the customer journey and identify key patterns that affect sales. Once these patterns are identified, organisations can better understand the customer journey and address pain points that are turning customers away. With consumer analytics, organisations can tackle the weak points in a customer’s journey and pave the way for smoother customer transactions.

In fact, we will see the entire business chain transform from a linear supply chain to a data-sharing model where suppliers, organisations and customers understand the value of data and cooperate with one another to meet their own objectives.

Transforming an organisation’s relationship with data

Organisations often store data in silos, however with consumer analytics, organisations will be forced to change their data storage methods, given that analytics will encourage organisations to move data away from information silos into data lakes while machine learning algorithms can run on these data lakes to reveal unexpected findings. Storing data in a data lake also allows organisations to make better use of real-time streaming.

For example, instead of drawing up a report to better understand what happened and make a decision, organisations can use data lakes to empower their employees, so they can make more informed decisions while working. The importance of data lakes becomes even more important when you consider the potential sources of data, which includes IoT and mobile networks.

Consumer analytics is the future

Consumer analytics is not just transforming the way businesses operate, it is paving the way for brand new business models that will transform business-consumer relationships. The conventional linear business relationship between organisations and consumers is changing and giving way to a two-way dichotomy, where both parties cooperate for mutual benefit. We are seeing an age where the customer journey is personalised thanks to certain practices, like dynamic pricing that were not possible without analytics. All these factors and more are sure to transform business models.