A good customer analytics software must be part of your business intelligence suite. Why? Because customer analytics tools help you understand your buyers better, along with their customer journey, customer lifecycle, buying patterns, communication preferences, and so on. Neil Patel goes as far as suggesting that understanding customers is the only marketing strategy you need

In the era of marketing automation and extreme personalization, customer intelligence must be the central pillar of your business’ growth. It’s the only way you can deliver truly unique and engaging customer experiences (CX), which is the top priority for most businesses in the next 5 years. A customer that has had a positive experience with your brand is more likely to spend more with your business, recommend your products/services to others, and come back to you every time they have a chance. People are also more inclined to pay a larger sum of money for a better experience. Thus, it may come as no surprise that, by the end of 2020, customer experience will have overtaken the price and the product as the key brand differentiator.

How can you distinguish yourself in such an overcrowded market and the best possible customer experience across all touchpoints? By choosing the best customer analytics solutions. In this article, we will explain what the basic types of analytics are, what is the most suitable customer analytics software solution for your business, as well as how you can use them in project management, customer engagement, and customer experience management and we will also answer some of the most frequently asked questions around this topic: 

  • How do you conduct a customer analysis?
  • What is customer service analytics?
  • What are the top analytics tools?

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Customer analytics solutions

You need them for a lot of reasons and they come in all shapes and sizes. There are many types of customer analytics solutions out there. We are talking here about data analytics software that helps you assess how healthy your business is and how well your online store is performing by looking at the whole situation through the consumer lens that is, through detailed consumer insights. According to Bit.AI, some of the best customer analytics tools and software available in 2020 include Mixpanel, Google Analytics, Kissmetrics, Woopra, Hotjar, Zoho Pagesense, Crazyegg, Brand24, Brandwatch, and Sprout Social

Each of them does different things: Mixpanel, for example, is a behavioral analytics platform for web and mobile, while Hotjar offers heatmaps for your website that essentially tell you how users are engaging with it, and Brandwatch is a useful tool for reputation management, offering information that ranges from crisis and brand management to competitive analysis and influencer marketing. 

The benefits of customer analytics platforms can’t be ignored: you can combine them with other software, such as your CRM or the tools you’re using for handling customer service, to get more complete and accurate insights about your customers. At the same time, you can use it along with your business intelligence software (that set of tools used by companies to retrieve, analyze, and transform data into useful business insights) for increased efficacy. The insights obtained this way can then be used to boost the productiveness of your automation software (and virtually any other kind of marketing software) to boost their efficacy and help you deliver the kind of experiences your customers love, thus preventing customer churn.

Customer analytics examples: how big companies use customer data to improve various areas of their business

  1. A first example of how companies use big data and customer data strategically is Coca-Cola and their digitally-led loyalty program they implemented in 2015. to strengthen its data strategy and boost customer retention. Here’s what Justin De Graaf, Director of Data Strategy and Precision Marketing at The Coca-Cola Company, had to say in an interview for ADMA about the program and the role it plays in remaining relevant and staying connected to its consumers in the age of digital transformation:

    “Data plays an increasingly important role in marketing and product development. Consumers do a great job of sharing their opinions with us – either by phone, email, or social networks – that allow us to hear their voice and adjust our approach. We often talk about why we have two ears and one mouth – it’s better to listen more than we speak. This holds true with our approach to consumer input. Data is also helping us create more relevant content for different audiences. We want to focus on creating advertising content that speaks differently to different audiences. Some people love music. Other people watch every sport no matter what time of year. Our brands are already visible in those spaces, and we’re working hard to use data to bring branded content that aligns with people’s passions.”
  1. With almost 200 million subscribers worldwide, it’s no surprise that Netflix has access to large amounts of customer data that it uses to improve the service and the streaming experience. They use customer analytics and artificial intelligence to develop not only a powerful algorithm that offers the best tailor-made recommendations to each viewer but also a long-term video content strategy that appeals to each audience around the globe. According to Toolbox, Netflix knows which series you are watching and for how long you continue watching it, or at what point you switch to something else. If let’s say, 70% or more users who started watching, finished all seasons of a canceled show, Netflix will decide to launch another season, as this data shows greater chances of people watching the new season as well. This is how you successfully use data-backed insights to keep your user base happy and engaged for a long time.
  1. It’s no secret that Amazon has a powerful algorithm as well- a recommendation engine if you will- that gathers huge amounts of data about users and their behaviors, not only in terms of buying preferences but also in terms of browsing, time spent on site, time spent on each product page, and so on. This way, their marketing and sales teams can get a 360-degree view of the consumers that can be used for making better product recommendations and providing a better on-site experience, as well as for lookalike-modeling to reach out to other similar people with product recommendations.

Best customer analytics software

There are numerous customer analytics software vendors on the market. Most of them are built on the same principles, gathering the same kind of information about your clients, their online preferences, and their buying patterns. But not all customer analytics tools are created equal. Some offer more information than others. Some help you predict customer behavior based on in-depth insights about your consumers (Reveal by Omniconvert is one of them), while others focus extensively on the buyer’s journey, like the customer journey analytics platform from Adobe

Google Analytics

It all comes down to the specific needs of your business. But we’re here to help you make better-informed decisions so we’ll focus on two main customer analytics platforms: Google Analytics, perhaps the most popular one, which is used by hundreds of millions of websites and eCommerce stores across the world, and Reveal by Omniconvert, which is more like a customer intelligence platform than your regular data platform.

Google Analytics can be a powerful customer analytics platform if used correctly. It offers access to various metrics and data points, like product performance, sales performance, events, multi-channel funnels, site speed, users & interests. Standard and advanced reports include:

  • Bounces
  • Entrances
  • Exits
  • Goal completions
  • Goal value
  • New users
  • Pageviews
  • Product Adds To Cart
  • Product Checkouts
  • Product Detail Views
  • Product List Clicks
  • Product List Views
  • Product Refund Amount
  • Product Refunds
  • Product Removes From Cart
  • Product Revenue
  • Quantity
  • Quantity added to cart
  • Quantity checked out
  • Quantity refunded
  • Quantity removed from cart
  • Refund Amount
  • Session duration
  • Sessions
  • Shipping
  • Tax
  • Time on Page
  • Transaction revenue
  • Transactions
  • Unique Pageviews
  • Unique Purchases

Of course, apart from the standard reports, you can set up your own personalized reports, with custom filters that show you the data that matters most to your business. But there are limited options when it comes to combining and correlating various dimensions and metrics. On top of it all, the most “revealing” reports are those that you customize yourself and it might be hard to successfully set up personalized reports without a thorough knowledge of the platform and its mechanisms.

In terms of “customer intelligence”, what you can get from Google Analytics relates mainly to transactions history: demographics, traffic sources and medium (campaign type, referral), the device from which your website is accessed, as well as the operating system, the user type (first-time or returning), and personalized targeting (targeting specific users on your site based on their cookie ID and Google Account if the user opts into these features; this targeting type may also include contextual targeting when we don’t have access to user data).

Reveal by Omniconvert

Among other customer analytics software vendors, Reveal stands out as a unique Customer Value Optimization Platform that helps e-commerce businesses with automated insights into customers’ buying behavior, segmentation, NPS, and lifetime value. It is a one-stop-shop solution offering you everything you need to know about your customers, their behavior, and their value on simple, intuitive dashboards. No more correlating data points extracted from multiple sources and software solutions, no more hassle in building customized reports and working with complicated analytics platforms.

You will no longer need to spend time and resources to dig into your data because once installed, Reveal will be able to give you the most important Customer Retention metrics:

  • RFM segmentation
  • NPS Score Monitoring
  • Buying Behaviour
  • Ongoing Personalization

The pillars on which Reveal is built are related to understanding your customers, monitoring their behavior across time, and nurturing the relationships you have established.

Understanding

  • Who’s your ideal customer profile
  • What made people buy from you
  • How often they buy certain products
  • What made some of them stop buying
  • Which are the most important brands, categories, customers
  • Buying patterns & Assortment anomalies

Monitoring

  • The retention rate
  • The lifetime value
  • The customers that matter with RFM Segmentation
  • Cohorts of your best customers
  • VoC: Customer effort, Customer Satisfaction, NPS
  • The most profitable segments of customers

Nurturing

  • Personalize their experience on website, email, ads, etc.
  • Prioritize the customers that matter
  • Solve their problems faster

This way you can empower your growth team with unified insights about your customers’ behavior. The setup process is easy and seamless as well: you can install the app from the Shopify store (for free until 31st of december 2020) OR upload your files in a JSON or API format, wait for the platform to crunch the data and turn it into insights, and get ready to get to know your consumers down to the smallest details.

The insights you obtain can be used to understand how you can improve your customers’ experience, reduce customer churn, and increase their lifetime value. Plus, they are organized in dashboards that are easy to work with and interpret by anybody working on your team- from your salespeople to product developers, the marketing department, and the management. Last but not least, through this way of interpreting your data, you can also predict trends and evolutions in buying patterns and consumer behavior so you could say that, apart from being a customer intelligence platform, Reveal is also, to a certain extent, a predictive analytics platform.

Why are we saying this? Because Reveal segments are a bit more complex than those you have been used to: you can see the potential in new customers (“Passionate new guys”– the ones who have placed their second order and already boasts a high average order value, or “Flirting”– the ones who have placed more than 3 orders of high value), as well as in your frequent buyers (“Potential lovers”– those who have placed more orders than the “Flirting” ones and are qualified to become active customers, “Lovers”– those who are active and have placed a good amount of orders of significant value, and “True Lovers”– your most frequent buyers who have placed the highest number of orders and the highest value). But you can also discover at-risk segments, like the “About to dump you” segment (comprised of those who are rather inactive, having bought from you more than half a year ago) and the “Breakup” segment (comprised of inactive, low-value spenders).

The predictive CLV (Customer Lifetime Value) can forecast how much revenue your customer will bring according to your historical data. 

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Klaviyo

You will also find lots of complementary tools that work hand in hand with these customer analytics platforms. Klaviyo, for example, is a great solution to interact with the clients based on the insights gained with Reveal. Klaviyo is a platform that offers listening solutions, as well as advanced personalization options for your communication, features dedicated to social advertising, and marketing automation. 

Customer experience always comes first. And having access to actionable insights is great but you also need additional solutions to help you put these insights at work. Klaviyo helps you delight customers with highly relevant messages, automate prospect and customer communications using customer lifetime value, lifecycle stage, and more, as well as dynamically transfer data to and from Facebook and Instagram to create relevant messages, deliver consistent experiences, and build stronger relationships.

FAQ related to the topic of customer analytics

How do you conduct customer analysis?

This operation is done with the main purpose of identifying your best customers, study their characteristics, and extract insights that might help guide your business strategy, and drive growth for your business.

  • Identify who your current customers are. You can do that by accessing the analytics platform you are currently using.
  • Extract customer data from your analytics software.
  • Apply the filters available in your analytics software to refine the customer data (geographic filters, social network filters, first-time or returning customers, etc.).
  • Based on spending and the customer lifetime value, you can then segment them into groups that are relevant to your business and your long-term goals.
  • Discover who your best customers are and what products/brands that are available on your shop they prefer (with Reveal, you can do this without any hassle, thanks to its intuitive and insight-rich dashboards).
  • Conduct an RFM (Recency, Frequency, Monetary value) analysis to understand more about consumer behavior and refine the customer segments you already started building once you started applying filters onto your customer data.
  • Customers segments come in all shapes and sizes. Reveal’s types of consumers are incredibly detailed and help you understand not only the behavior of your current customers but also the motivations of those who have left you. Moreover, the segmentation mechanism used by Reveal to build the customer segments will also help you better understand their customer journey. All of this without any other operation required from your side.
  • Determine your customers’/customer segments’ net promoter score (NPS)- it is a measure of customer satisfaction that offers you insight into how well you have crafted the customer experience and how much your customers enjoy doing business with you. 

What is customer service analytics?

Customer service analytics is the process of collecting and analyzing various types of customer feedback to discover valuable insights. It can also be described as another kind of customer data analytics, one that is more customer-oriented and gives you more insight into their behavior than the regular customer analytics platforms.

It can help you better understand your customers’ needs and expectations, lead to enhanced, more refined customer experience strategies, and, ultimately, increase customer loyalty and encourage retention. Data can be extracted from the support tickets, NPS surveys, customer feedback gathered from various sources, as well as from your CRM platforms. Customer service analytics completes the overall view you have on your clients, by adding the dimension of customer experience and satisfaction. 

What are the best analytics tools?

There is no such thing as the “best analytics tool”. It all depends on what kind of data you are analyzing and what your business objectives are. There are highly popular and fairly comprehensive platforms such as Google Analytics, but there are also lesser-known, more powerful tools, such as Reveal by Omniconvert, that allow for a more detailed and granular view of customer behaviors and buying patterns. If you are interested in analyzing the performance of your website, Hotjar is a highly relevant tool. If, on the other hand, you want to monitor conversations happening around your brand, and protect its reputation, then Brandwatch is the go-to solution. If social media is your priority, then Social Sprout is a great tool that combines analytics with listening and engagement tools, as well as with publishing and scheduling integrations.

As you can see, there are countless analytic solutions on the market but there’s no single one that does it all. At the end of the day, it all comes down to your specific needs and expectations.

Conclusions

In today’s article, we talked about different types of customer analytics software and the way they can help you grow your business. We saw how important customer intelligence is nowadays and how various brands leverage it to create better products and designs better experiences for their clients, as well as how these insights can help you reduce customer churn, and increase customer lifetime value by leveraging the customers’ wants and needs in a smart way. We made a comparison between the most popular analytics platform on the market- Google Analytics- and a new entrant, with more refined capabilities, namely- Reveal, by Omniconvert. We also answered some frequently asked questions directly linked to customer analytics and we understood that there’s no single “best solution” when it comes to analytics software. We hope that by now it got clearer how you should approach customer analytics and what you should take into account while choosing the right platform for your business.


Meanwhile, you can try Reveal for free until 31st of December (offer available for Shopify Stores). Or you can get a 30-days free trial for other platforms. Leverage the power of customer data and good insights and see how it can transform your business!

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