Clickstream Analytics: A Gamechanger for eCommerce
Tags: webdev, ios, android, rudderstack
Published: 2020-02-17 16:28:35

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<p>Today, websites and mobile applications have become the digital storefronts of every eCommerce company. This move to the digital platform has lowered the entry point to establish a retail business. It has also made time and distance irrelevant in the pursuit of customer acquisition and sales. However, the loss of the in-person interaction has also introduced some new and unique challenges such as ensuring good conversion rates, optimizing the customer experience, and more. <strong>Clickstream Analytics </strong>has proved to be a vital tool in addressing these challenges faced by the eCommerce industry.<br></p>
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<p>In this article, we will dive into what Clickstream Analytics is, what it does, and why it is so useful for the eCommerce businesses.</p>
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<h2>What is Clickstream Analytics?</h2>
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<p>Simply put, a <strong>clickstream</strong> is a sequence or stream of events that represent user actions (clicks) on a website or a mobile application. However, in practice, the scope of clickstream extends beyond clicks. It includes product searches, impressions, purchases, and any such events that might be of relevance to the business.<br></p>
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<p>Traditionally, such type of event collection on websites is done through the use of JavaScript-based trackers. These trackers send POST requests to the remote <strong>collector </strong>servers and then store the incoming data in formats appropriate for consumption by the analytics systems.<br></p>
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<p>Now that we understand what clickstream analytics is, let us look at how clickstream analytics addresses some of the challenges we mentioned at the start of this post, namely:</p>
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<ul><li>Ensuring good conversion rates</li><li>Enhancing customer experience</li><li>Optimizing digital marketing spend</li><li>Up-selling and cross-selling</li></ul>
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<h2>Conversion</h2>
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<p>Various surveys/researches have pegged <strong>conversion </strong>(a user session actually culminating in purchase) to anywhere between <a href="https://www.invespcro.com/blog/the-average-website-conversion-rate-by-industry/">2% - 3%</a>. This is despite the fact that any eCommerce site provides some kind of product recommendation to its customers.&nbsp;<br></p>
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<p>Typically, there are specialized Recommender Engines and/or Market Basket Analysis systems that are responsible for making such recommendations to the customers. However, both of these tools suffer from some inherent weaknesses. These methods essentially leverage the ‘past purchase’ behavior of users to provide recommendations. Also, they only consider the purchase once it is completed, and do not take into consideration the users’ train of thought leading to that purchase. An individual user’s purchase propensity might not always be in sync with the other users in the same segment or category.<br></p>
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<p>Clickstream data can be really effective in capturing the user’s browsing pattern, which can then be leveraged to predict page displays that will lead to a likely purchase.</p>
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<h2>Improving product experience to enhance Customer Experience and Customer Journey</h2>
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<p>Clickstream data can be combined with another website/application-specific data to enhance customer satisfaction in one or more of the following ways:<br></p>
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<ul><li>Using standalone records of clickstream data can help in <strong>performance analysis</strong>, such as identifying products or pages that attract most user visits, where users spend more time on the site or the app, etc. This analysis can then be used to optimize the platform or the product.</li><li>Clickstream data contains information such as the URL of each page visited by the customer, the date and time when the page was visited, as well as how long it took for the page to load. In the event of negative customer feedback related to the website or the app - such insight into the customer's site navigation can be of immense help in identifying potential causes of dissatisfaction. For e.g. high load time for some pages.</li><li>Combining the timestamp and URL from the clickstream data - a customer’s sequence of page visits can be constructed. This sequence can then be analyzed to optimize the website layout to ensure that customers are able to get to their desired pages with the least number of clicks.</li><li>In cases where customers are searching for a product, the search query can also be sent along as part of the clickstream data. Text mining techniques can then be applied to the query data to better understand it, and route the customer to the desired product much faster.</li></ul>
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<h2>Optimizing Digital Marketing Spend</h2>
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<p>Distribution of the marketing budget should be driven by inferences based on the customers’ propensity to respond to digital campaigns and banners. Clickstream data can help achieve that in the following ways:</p>
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<ul><li>Determining what percentage of traffic is being directed by banners or campaigns.</li><li>Determining the effectiveness of the banner or campaign by analyzing the traffic attracted by the banner or campaign. This can be done stage-wise (e.g. Product View, Cart Addition, Checkout, Purchase) considering both successful transitions to the next stage in conversion funnel as well as exits.</li><li>Identifying the banners or campaigns that have contributed to faster conversions</li><li><strong>Clickstream timestamps </strong>can be leveraged to determine which campaigns/banners are more effective at what time during the year, month, or day. They can also be used to determine the amount of time spent by users visiting the site via the banners/campaigns vis-a-vis the overall trends</li></ul>
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<h2>Upselling and Cross-Selling</h2>
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<p>In eCommerce, upselling refers to the practice of encouraging the customers to buy a higher-end version of the product that the customer prefers, preferably a notch above the usual pricing segment. Cross-selling refers to recommending the customers to buy related or complementary items, for e.g. recommending headphones when the customer is looking to buy a phone.&nbsp;<br></p>
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<p>Clickstream data can be used to facilitate such kinds of cross-selling and upselling, with the help of various clustering algorithms. These algorithms can use different dimensions of the clickstream data such as user demographics, browsing and purchasing pattern, price preferences, etc. as features to build an appropriate model. This model can then be used to recommend appropriate products to the customers.</p>
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<h2>The Role of CDI in Delivering the Power of Clickstream</h2>
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<p>Clickstream Analytics is an invaluable tool for eCommerce companies in their quest for increasing sales, delivering greater customer satisfaction and thereby enhancing their shareholder value. While there are plenty of tools that empower enterprises to mine their clickstream data to deliver its fullest potential - the challenge of integrating such tools with their existing infrastructure often holds back companies from whole-heartedly embracing the power of clickstreams. Then there’s the issue of ensuring complete data privacy and ownership of their data. Hence, there is a growing trend among the businesses to gravitate towards<strong> Customer Data Infrastructure (CDI) </strong>tools and platforms, which can provide these enterprises with a single gateway to the analytics platforms of their choice.&nbsp;<br></p>
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<p><a href="https://rudderstack.com/"><strong>RudderStack</strong></a><strong> </strong>is an open-source CDI platform that gives businesses the freedom to capture and route their clickstream data from their website or mobile app to their preferred third-party analytics platforms such as Google Analytics, Amplitude, MixPanel and more, ensuring data privacy and complete control of their data at the same time.<br></p>
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<p>If you are an eCommerce business looking to get the most out of your clickstream data, you should definitely check us out. To know more about RudderStack, please <a href="https://rudderstack.com/contact/">contact us</a> or <a href="https://rudderstack.com/request-a-demo/">sign up for a free demo</a>.<br></p>
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