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Understanding Omnichannel Analytics

How do customers experience your business? It can be hard to know! For example, a person might notice a product on social media, search for information on Google, visit a physical store, chat with representatives online or over the phone, and visit several websites before making a purchase using a store app. The bigger the purchase, the more likely they are to do some legwork, and the harder it is for companies to know what their customer journey was and how they experienced it. 

Omnichannel analytics attempts to play the sleuth, helping businesses to know the route customers follow before committing to a purchase. Your business can use that information to make each step easier, pleasanter, and more compelling. It can also analyse and personalise individual experiences, creating a “conversation” between your business and prospective customers instead of allowing each interaction to occur in isolation. Let’s try to be more specific by formulating a definition.

What is Omnichannel Analytics?

Omnichannel analytics are reported by synthesising information across platforms and sales channels and presenting them in one place. Instead of focusing on channels, they focus on customers, attempting to determine what leads them to purchase, and what acts to deter them from purchasing. Getting these analytics requires the use of specialised software or tools. Additional uses include:

  • Predicting demand per product
  • Troubleshooting stock levels
  • Recommending strategies for cost savings and increased sales
  • Unifying data to allow teams to function cooperatively

Why are Omnichannel Data Analytics Important?

You’ve already spotted that omnichannel analytics can help you improve customer experiences, help with inventory decisions, and indicate strategies that improve profitability. That’s important enough to begin with, but there’s more to it than that. 

You’ll be able to fine-tune your marketing strategies by understanding customer preferences and motivations better. You may identify bottlenecks and sticking points, giving you an opportunity to remove obstacles to purchasing. Besides this, you might spot elements which, though they don’t directly make sales, are essential contributors in customer decision making. 

In short, you’ll be able to plan marketing, selling and fulfilment with a focus on what works for your business and its customers. Instead of just trying to guess, you’ll know where your resources can best be allocated. And, you might be in for some surprises along the way. Trying to gather, synthesise, and analyse all this data by hand isn’t practical, but with software doing the legwork, you’ll get better insights from your data and you can even follow it in real time. 

Tools for Omnichannel Analytics

With a growing number of businesses understanding the importance of omnichannel analytics, software companies are in a fierce battle to produce the ultimate analytics tools. Some are producing tools focussing on specific areas. Others try to offer all-in-one solutions with greater or lesser success. 

To choose the right omnichannel analytics tools for your business, develop a set of selection criteria rather than simply opting for anything carrying the omnichannel tag. 

  • Begin by considering what data you hope to synthesise, what you hope to find out, and what you want to achieve. 
  • Evaluate the type of reports the tools generate, and whether they present data in a form that provides the insights you’re seeking. 
  • Consider ease of use. If your tools are too complex to work with, they’ll have limited usefulness.
  • Decide whether the cost of these tools justifies the benefits of using them. 

How to Implement Omnichannel Analytics

Tools and information are only helpful when they are used properly. Once you’ve chosen your toolkit, your first step will involve allocating responsibility and ensuring that the people who are to use the tools know how to do so. Questions to answer might include what insights you want, how frequently data should be monitored, where and how results will be reported, and who is responsible for recommending and initiating actions that flow from the insights gained. 

Since reports and conclusions are only as good as the data sets from which they are drawn, you’ll also have to consider your approach to data governance. Besides this, the information you gain, and the way you react to it will impact people across the organisation. They may have perspectives that can contribute to decision-making and execution. For example, your marketing team might use omnichannel marketing analytics and determine that a particular product deserves promotion – but that impacts production and fulfilment. Form cross-functional teams that allow for coordination. 

Monitor performance to see whether you’re achieving what you set out to do and make adjustments along the way. Are the tools providing useful information? Are reports being used to make good decisions? Could you do even better?

Challenges for Implementing Omnichannel Analytics

Customer Journeys Can Be Complex 

Even when entire customer journeys happen online, they can be very complicated. For example, you may not know how individual customers became aware of your products, especially if they don’t initially interact. Part of their journey may be happening offline, and the channel they use to purchase your products may not be the one that initially drove the sale. Always be aware that you might not know every single step of the customer journey, even though you have omnichannel analytics that help you pin down some of the most important components. 

Data Integration and Accuracy

The tools you use must integrate data from multiple sources – and for the conclusions to be relevant, accurate data is crucial. However, accuracy is only one factor to consider – synchronisation of data is also important. For example, you may benefit from synchronising customer data with competitor-related data, inventory data, and more. And, of course, you don’t want to start over with a full range of new systems, so compatibility with the software you already have also comes into play. 

Data Privacy and Security

Your aim is to develop personalised customer journeys, serving your customers better. But beware of falling afoul of data privacy laws. If you’re going to gather data, your customers are entitled to know what information you’re gathering, how you’re using it and why, and they are fully entitled to decline. With data comes responsibility for its security, especially if it includes sensitive information like names and contact details. 

Unifying Channels and Eliminating Silos

It’s not just information that has to be consolidated for omnichannel analytics to be useful. The channels themselves must work together. For example, if you sell from a website, a brick-and-mortar store, and an app, and communicate with customers on social media, decisions impacting one of these elements may affect the others. And, since customers switch channels freely, you must be sure that their experiences across channels are consistent. 

Managing Change

Just having synthesised data is useless. Taking action based on data implies change. Sometimes, it’s just a matter of a few tweaks, but at others, it will involve significant changes to the ways in which you work. Managing change is rarely easy, and the bigger the changes, the harder and costlier it gets.  

AI and Omnichannel Analytics

AI is key to acquiring conclusions and recommendations based on the huge amounts of data that go into omnichannel analytics. Apart from collecting and analysing data, it draws attention to patterns, helping you to gain further insights into customer behaviour. Omnichannel historical analysis helps AI to make important predictions, for example, sales projections. It helps you with elements of strategy too. As an example, it can use market info to recommend pricing strategies. On a smaller scale, AI automates individual customer experiences, leading customers through the purchasing process based on its analysis of their behaviour. 

Although there are obstacles and imperfections to navigate, AI-driven omnichannel analytics can help you make data-driven decisions, improve customer experiences, and help you grow your business.  

Human Interactions and Omnichannel Analytics

No matter how far tech takes us, interpersonal interactions remain among the most important sources of information for your business. It’s not just what people say, but what one can infer. For example, if people consistently contact your support agents, regardless of channel, with specific requests for product information, or particular issues, it’s a call to rethink and improve specific components that go into customer journeys. 

In all the excitement about automation and AI, never forget that what you’re ultimately aiming for is a better understanding of human behaviour. Although technology can uncover some of the information you’re looking for, the things your customers say and the solutions that satisfy them are best gauged in one-to-one interactions. It’s data you can’t afford to miss out on, and you need this information to guide your decision-making.

At RSVP, we monitor our clients’ omnichannel communications around the clock, dealing with customer enquiries and calls for support across platforms. When people reach out, they’re at a particularly delicate stage of their customer journeys. We give them the service they need to turn their experiences into positive ones, and we use advanced software to capture the data you need. 

Struggling to support your omnichannel retail efforts? Get our London-based omnichannel call centre on your side. Your customers get unparalleled service and support, and you get the all-important analytics and intel. Talk to us about your omnichannel strategies today. 

 

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