Optimising Omnichannel Analytics: Extracting Insights to Inform Strategic Decisions

Why omnichannel analytics matter for your business

In today’s fast-paced digital world, businesses need to be everywhere their customers are. This means having a presence across multiple channels, from physical stores to online platforms and social media. But just being present isn’t enough. To truly succeed, businesses need to understand how these channels work together and how customers interact with them. This is where omnichannel analytics come in.

Omnichannel analytics help businesses gather data from all their channels and combine it into a single, comprehensive view. This allows businesses to see the bigger picture and make informed decisions. For example, a customer might browse products on a website, check reviews on social media, and then make a purchase in-store. With omnichannel analytics, businesses can track this entire journey and understand what drives customer behaviour.

Key metrics to track in omnichannel analytics

When it comes to omnichannel analytics, there are several key metrics that businesses should track. These metrics can provide valuable insights into customer behaviour and help businesses make data-driven decisions. One important metric is customer lifetime value (CLV). This measures the total value a customer brings to a business over their entire relationship. By tracking CLV, businesses can identify their most valuable customers and tailor their marketing efforts accordingly.

Another important metric is customer retention rate. This measures the percentage of customers who continue to do business with a company over a specific period. A high retention rate indicates that customers are satisfied and loyal, while a low retention rate may suggest that there are issues that need to be addressed. Other key metrics to track include conversion rate, average order value, and customer satisfaction score.

Tools and technologies for effective omnichannel analytics

To effectively track and analyse omnichannel data, businesses need the right tools and technologies. One popular tool is Adobe Analytics, which provides advanced analytics capabilities and real-time insights. Adobe Analytics can help businesses track customer interactions across multiple channels and gain a deeper understanding of their behaviour. Another useful tool is Adobe Experience Manager, which allows businesses to manage and deliver personalised experiences across all their channels.

In addition to these tools, businesses can also benefit from using a product information management (PIM) system like Akeneo PIM. A PIM system helps businesses manage and centralise their product data, making it easier to track and analyse. By integrating a PIM system with their omnichannel analytics tools, businesses can ensure that their data is accurate and up-to-date.

How to integrate omnichannel analytics with your existing systems

Integrating omnichannel analytics with your existing systems can be a complex process, but it’s essential for getting the most out of your data. One way to do this is by using an enterprise resource planning (ERP) system like Epicor BisTrack. An ERP system can help businesses manage their operations and streamline their processes. By integrating your omnichannel analytics tools with your ERP system, you can ensure that your data is consistent and accurate across all your channels.

Another important integration is with your customer relationship management (CRM) system. A CRM system helps businesses manage their customer interactions and relationships. By integrating your omnichannel analytics tools with your CRM system, you can gain a deeper understanding of your customers and personalise your marketing efforts. Here at iWeb, our talented in-house team can help you with these integrations and ensure that your systems work seamlessly together.

Best practices for analysing omnichannel data

When it comes to analysing omnichannel data, there are several best practices that businesses should follow. One important practice is to focus on the customer journey. By tracking and analysing the entire customer journey, businesses can gain valuable insights into customer behaviour and identify areas for improvement. For example, if customers are abandoning their shopping carts at a high rate, businesses can investigate the reasons behind this and make changes to improve the checkout process.

Another best practice is to use data visualisation tools to present your data in a clear and understandable way. Data visualisation tools can help businesses identify trends and patterns in their data and make it easier to communicate their findings to stakeholders. Additionally, businesses should regularly review and update their analytics strategies to ensure that they are keeping up with the latest trends and technologies.

Case studies: Successful omnichannel analytics implementations

Many businesses have successfully implemented omnichannel analytics and seen significant benefits as a result. One example is a leading UK retailer that used Adobe Analytics to track customer interactions across their website, mobile app, and physical stores. By analysing this data, the retailer was able to identify key touchpoints in the customer journey and optimise their marketing efforts. As a result, they saw a 20% increase in conversion rates and a 15% increase in customer retention.

Another example is a global e-commerce company that used Akeneo PIM to centralise their product data and improve their omnichannel analytics. By integrating Akeneo PIM with their existing systems, the company was able to ensure that their data was accurate and up-to-date. This allowed them to gain a deeper understanding of their customers and personalise their marketing efforts. As a result, they saw a 25% increase in average order value and a 30% increase in customer satisfaction.

Challenges and solutions in omnichannel analytics

While omnichannel analytics can provide valuable insights, there are also several challenges that businesses may face. One common challenge is data silos. When data is stored in separate systems, it can be difficult to get a complete view of the customer journey. To overcome this challenge, businesses should focus on integrating their systems and centralising their data. This can be achieved by using tools like Adobe Experience Cloud and Akeneo PIM.

Another challenge is data quality. Inaccurate or incomplete data can lead to incorrect conclusions and poor decision-making. To ensure data quality, businesses should implement data governance practices and regularly review and update their data. Additionally, businesses should invest in training and development to ensure that their teams have the skills and knowledge needed to effectively analyse and interpret their data.

Future trends in omnichannel analytics

As technology continues to evolve, there are several trends that are likely to shape the future of omnichannel analytics. One trend is the increasing use of artificial intelligence (AI) and machine learning. These technologies can help businesses analyse large volumes of data and identify patterns and trends that may not be immediately apparent. For example, AI can be used to predict customer behaviour and personalise marketing efforts.

Another trend is the growing importance of real-time analytics. With the rise of digital channels, customers expect businesses to respond quickly to their needs. Real-time analytics can help businesses track customer interactions in real-time and make immediate adjustments to their strategies. This can lead to improved customer satisfaction and increased sales. Here at iWeb, our expert developers are always staying up-to-date with the latest trends and technologies to ensure that our clients stay ahead of the competition.

To learn more about how we can help you optimise your omnichannel analytics and drive your digital transformation, contact iWeb today. Our talented UK team is here to help you every step of the way.