A Guide to Omnichannel Analytics & Reporting
We overview some of the key considerations and tools you need for omnichannel analytics and reporting.
We overview some of the key considerations and tools you need for omnichannel analytics and reporting.
Omnichannel analytics is the practice of gathering and analyzing data on customer interactions across all the channels your business uses. The purpose of this analysis is to give customers a seamless, personalized experience as they transition from one touchpoint to another.
When you invest in omnichannel personalization, you boost your bottom line. After we surveyed over 3,000 businesses and customers across five continents, we found that 49% of consumers would buy again from a brand after a personalized shopping experience. On the other hand, 62% of consumers said a generic experience was enough for them to move on from a brand for good.
Daryl Bowden, Executive VP of Technology at Fox Corporation, describes omnichannel personalization this way: “When you use any of our apps, you should be greeted like an old friend. When we deliver an ad to you, it should be relevant. When we suggest content to you, it should be in line with your tastes.”
Fox achieves this by giving all customer-facing teams access to a single source of truth for all customer data, no matter what channel the information came from. That’s omnichannel analytics and reporting in action.
Say a customer visits your website and responds to a chatbot on your homepage. The customer expresses interest in one of your products, and the chatbot hands them off to a sales rep for a phone call. The sales rep shouldn’t have to ask what product the customer is interested in – they should build on the previous conversation, even though it happened in a different channel.
This example is just a small facet of the omnichannel experience, and it’s dependent on omnichannel analytics and reporting. Marketers analyze customer experiences day in and day out to:
Prevent data silos – Omnichannel analytics and reporting prevent data silos by revealing customer behavior and interactions across channels.
Gain a 360 view of the customer journey – With omnichannel analytics, you see how (and where) a customer has interacted with your brand. Going with the example above, a sales rep might have the added context of the customer’s chatbot session and behavioral data that shows a customer has been reading certain online documentation. (Insight a sales rep could use to customize their pitch.)
Create omnichannel customer experiences – With the insights gained from omnichannel analytics, you can then design personalized customer journeys to improve engagement and conversion rates.
In our annual personalization report, we found that only 35% of companies believe they’re successfully achieving omnichannel personalization. The two main barriers to success? Businesses were lacking the right technology and accurate, real-time data.
To create a data infrastructure that supports successful omnichannel personalization, start with the following tools.
Customer Data Platforms (CDPs) like Twilio Segment bring together first-party data from multiple sources – like your website, app, email, brick-and-mortar stores – to create unified customer profiles that are updated in real time.
Data analytics tools help you investigate specific parts of the customer experience. For example, a sentiment analysis tool like Qualtrics analyzes what customers say about your brand on social media, review platforms, and in customer support conversations.
ETL is a method for data integration that stands for “extract, transform, and load.” First, you extract data from different sources, copy it into a staging area, and then transform it by masking personally identifiable information, reformatting data into a structured or semi-structured format, and so on.
Lastly, you load this transformed data into its intended destination (like a relational database or data warehouse) for ongoing analysis.
Learn how Twilio Segment integrates with ETL tools like Stitch and Serenytics.
Here are a few key steps that you need to take to implement omnichannel reporting and analytics.
On average, a mid-market company uses 185 different apps in their tech stack – which can translate to a lot of disparate data. Manually trying to consolidate all this data is a time-consuming endeavor that loses the advantage of being in real time.
Take it from DigitalOcean; they used Twilio Segment to offload the manual work of exporting data sets, and break down data silos. Here’s the full story.
A CDP does this automatically, sending data to a centralized repository (like a data warehouse), and to any downstream tool, so that companies are working with a complete view of the customer.
There are a few culprits behind “bad data,” but one we see quite often is: no standard naming conventions. The difference between “user_signedup” and “user_sign_up,” as small as that might seem, is enough to wreak havoc on your analysis.
To improve accuracy, create standard naming conventions to align everyone within your organization (whether they work in marketing, customer support, or product).
Learn more about establishing naming conventions for your data here.
A single customer view gives you an accurate view of your customer’s journey with your business. With a CDP, you don’t need to build this view manually. CDPs use identity resolution to identify the same customer across multiple channels based on the first-party data you’ve collected.
Choosing the right metrics to measure customer engagement is essential for accurate reporting. Too often, businesses fall into the trap of using vague benchmarks to measure success. For instance, to improve the overall lifetime value of your customers, you may want to focus reducing churn rates (along with encouraging more conversions).
We list out the essential customer engagement metrics you should be tracking in this guide.
Use customer journey mapping tools like UXPressia, or diagramming apps like Lucidchart, help visualize the different steps in the customer journey. This provides great insight into how people move between channels, weaker parts of the funnel, and your levers for you success.
Check out this guide to customer journey mapping to learn more.
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An omnichannel analytics approach might look like this: you analyze which channels a customer chooses to engage with, understand how an experience in one channel influences their behavior in another, and learn about their interests based on the products or articles they've viewed on your site. You can then use these insights to target that customer with relevant ads on their preferred channels.
The challenges of leveraging (and implementing) omnichannel analytics tend to be a lack of the proper technology, a disconnected tech stack (and as a result, data silos), or inaccurate data (e.g. no standard naming conventions).
Omnichannel analytics and reporting provide a 360 view of the customer, which enables businesses to create fluid, personalized experiences across all channels and touchpoints.
Twilio Segment’s CDP consolidates data from multiple sources and channels into a centralized database and unified customer profiles, which is updated in real time.