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[Column] Nick Durrant: New business opportunities with data analytics


Data driven organisations are in a better position to make better strategic decisions to increase operational efficiencies, improve customer satisfaction and ultimately higher revenues. They are far more likely to acquire and retain customers.

Data and analytics is disrupting traditional business models and ecosystems, helping modern organisations remain competitive. It provides business leaders with the insights to drive strategic business decisions by better understanding the dynamics of the business, customer trends, managing risks and anticipating market shifts.

With the vast array of analytical capabilities and techniques at their disposal, business leaders can now access and understand the benefits of digitising their processes. Digitising customer interactions can provide a plethora of information that can be fed into operations, strategy, sales and marketing, and product development.

Detailed data and analytics enables businesses to personalise their products and services. It also improves internal processes, managers now have valuable data available that can be used to improve resource allocations, operations, delivery, capacity planning and manufacturing.

Consumer information

With the right approach, analytics can provide a competitive advantage. Businesses now have an opportunity to use data and analytics to drive digital transformation and redefine the customer experience. However, to accomplish this, management must create a data-driven culture focused on delivering business outcomes.

There is no shortage of customer data, but it is imperative for organisations to use these insights to shape their products, solutions and customer experiences. Businesses that use their consumer behaviour insights strategically certainly outperform their peers in sales. It is therefore important that businesses consider the strategic importance of consumer information.

Businesses need to use data from CRM systems, marketing databases and social network discussions to determine market and customer needs. It will also help identify the future trends to form part of the data strategy.

User Experience (UX)

Collect user experience information from surveys and usability tests and use this data and analytics to improve existing offerings and refine any new designs. Make sure new and existing customers are happy and that they want to use your products or services, and tell everyone about it.

Personalisation

Data analytics helps personalise customer interactions. One could build a recommendation engine that analyses website navigation, past transactions and purchasing decisions by consumers with similar profiles. This enables businesses to offer each online customer exactly what they are looking for. Being demand-driven and customer-oriented are modern business prerequisites.

Advertising

Data analytics reveals the effectiveness of advertising. One can now view click-by-click data about which customer responded in which way to which advertising. This helps one to choose the right message and the correct channel for maximum effect and zero wastage.

Pricing

There is a fine balance between maximise profits and customer satisfaction. Predictive analytics helps one understand how different pricing strategies can work. This could include market trends, past sales records, seasonal trends or one could even analyse buying patterns of groups or individual accounts.

Future demand

Future demand sensing is crucial and directly influences sales, required inventory levels and customer service. Businesses can use this past sales data and predictive analytics to detect patterns, determine future demands and help organise the workforce accordingly. Forecasting is also often overlooked at the point-of-sale level, but if done correctly, it could improve cross department collaboration and distribution centre forecasts.

Inventory

Inventory management is a fine art, holding too much inventory is costly and having a shortage could mean lost sales and even customers. It is even more complicated for retailers, they need to optimise the array of products according to limited floor space. Data analytics will help find the right balance.

Order fulfilment

Order fulfilment is the complete process from point of sales to delivery of the product to the customer. Data analytics lets you make delivery promises that you can keep and that will ensure customer satisfaction and loyalty.

Delivery

Success will largely depend on final delivery and the performance of suppliers. One needs to track delivery quality and timeliness with real-time data analytics and dashboards. This will help one manage suppliers more effectively.

Using analytics to make powerful business decisions is critical, every business needs a data and analytics strategy.

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