Rafa

If you’re a small business owner running an e-commerce store or an e-store retailer or merchant, you would have, by any means, opted for either one of the two most popular e-commerce platforms: Shopify and Magento. There are a host of benefits that come along when merchants go for personalisation of Shopify and Magento environment. But any store owner would like to see the benefits of personalisation efforts in a clearer way as the platform traffic begins to surge.

One such merchant analytics suite is the Essential Insights, SaaS solution, which pulls together sales data from various shopping cart platforms and gives marketers an exact report of where a user goes and what they actually do, from websites, pages to search engines visited, purchases carried out and conversions made.

Interestingly, Essential Insights also provides recommendations and insights real time based on historical data analysis and more importantly, sales-boosters that could have a direct impact on the merchant’s top line.  By tracking the visitor’s Essential Insight such as the purchase behaviour, and understanding and interpreting the user preferences and taste profiles captured, the e-retailer or the merchant can tailor and personalise product offerings, deals, discount offers, cashbacks, rebates, etc in the best possible way.

The various offerings can be in the form of:

·         Displaying personalized product recommendation widgets on key pages (i.e., home, product list, product detail, basket, category, etc)

·         Displaying popular products or recently viewed products on selected web pages

·         Sending autoresponder e-mails upon the visitor initiating or taking a particular action

·         Integrating cross-sell and up-sell features

The results could have nearly astronomical effects on the way e-retailers and online merchants tailor the offerings: increased sales revenue, increased number of products sold, increase in the average order size of basket, enhanced conversion rate, reduced churn rate, tailored personalized user interface according to user preference, increased user retention, reduced cart abandonment, increased time on site and repeat sales.

The key to deriving real meaning from social data is to make a penetrative analysis of the interests and opinions of consumers. Information linked to demographics and other consumer essentials are great to have, but when it comes to sparking an emotional connect between your brand and your customer and kindling that interest which will reverberate with the target audience, Social insights is the perfect way to gain understanding about any and all parts of a marketing campaign.

Social insights help enterprises and organization map the customer’s entire purchase journey with the data they give you on social media, ensuring the right customer is targeted with the right message at the right time. Thanks to clickstream data, one can derive information using behavioural social insights to improve targeted aspects of an e-commerce portal or an e-store.

While e-retailers, online merchants and e-store owners should be listening across the entire customer purchase journey, the initial stages of planning to purchase a product online is when most brands and companies can utilise to the fullest and  up the ante.

Social insights has moved a notch higher by diving deeper into the data and not just generating social conversations. If we analyse social media conversation around the topic of shopping, we can easily identify what’s selling hot and what’s not online in ecommerce stores and retailer shops.

Brands can leverage rich social insights to discover how they can improve their service levels, what kind of offers, rebates, discounts and deals actually click. Listening to social interactions can help brands understand when to promote and when to apply the brakes. Social insights details the kind of content experience the customer would want to be dished out every time.

Understanding your customers through social insights paves the way to retaining them and improving Customer Lifetime value (CLV), which in turn, will hugely impact your business’s bottom line. It is important for retailers to identify all the possible touchpoints through the various Social insights and customer interactions. On a high level, interacting with the customer touchpoints can spell success in the long run.

If you are an online merchant or retailer, it is a tough play field out there with the brand bigwigs completely transforming the e-commerce sphere deploying Big Data, Artificial Intelligence (AI) bots, Machine Learning and modes of digital technologies. Clickstream Data has empowered brands, startups and small businesses alike to analyze data from various sales channels, and, in recent times, has helped drive several retailers towards real time insights and even empower them to automate their business decision using deep customer insights.  Shopping card abandonment is a worldwide phenomenon accounting to almost 74 percentage of the total transactions, according to a recent study. It is obvious that marketers are overlooking the solution.

Retailers who get into the abyss of clickstream learn how to segment customers and analyse which sites they hit before and after visiting their website. Metrics such as organic keywords, traffic boosters, and conversions industrywide help in the identification and segmentation of customer strata.

While UX teams know how their own path-to-purchase funnels, which is based on internal web analytics, work, the way they view how marketing campaigns are performing is quite restricted; Clickstream takes the data metrics to a different level.

Watch where do customers come from Whatever be the final touchpoint – account registration, subscription or a transaction confirmation, the last 10 pre-visit touchpoints (or the previously visited sites) is a must check. Marketers, then, should analyse trends for common paths or highest volume and detail the recurring websites or companies. The next step is to frame a strategy to ascertain which channels has the most engagement— whether it’s display, affiliate or data feeds — and either integrate targeting as part of the marketing campaign or touch base with companies discovered via the clickstream data.

Watch where customers go after leaving the website Where do customer go after making an exit from the site? Do they conduct more research? Do they hit a competitor’s site page? Clickstream data offers vital information for making useful re-engagement with audience members to convert them into potential buyers and nurture meaningful relationships. If supposing the next stop on their browsing journey is a third-party marketplace then it becomes the target site. By sticking to the same path of action for post-visit touchpoints as that of pre-visit touch points, you can find out customer behaviour post-transaction.

Measurement of third-party lift Determine the marketing campaign that needs to be measured, the distribution websites selling the merchandise and the required purchase window.  Next, crunch the clickstream data (or collaborate with a firm that can) and generate report on total transaction counts supported by the campaign or the overall surge in the conversion rate assuming the third-party conversions are factored in. Leverage your business model or CRM depending on these conversions to realize proper attribution weights.

Segment customers across range of industries Clickstream enables marketers to not only segment their customers, but also those of their competitors. A common method is to collect the sites that feature most commonly during browsing activity, and view the overlap across the industry. This data can hold sway over channel selection for all future marketing efforts, budget decisions and identification of new opportunities.

Focus on the right audience group Clickstream helps retailers to upgrade to audience buying using a demand-side platform or data management platform. Buying and targeting the right audience group generated from clickstream activity seeds for programmatic campaign activities is much easier. These audiences range between a standard set — people who have bought from major 10 retailers, for instance — and those that can be customised.

Whether you’re debuting a new platform or going for audience buying, clickstream data analysis offers fresh opportunities by providing multiple granular views of the business’s customer segments. Marketers need to analyze the customer’s clicks to view what the people are looking for that the competition deprives them of, then relate audience-buying and programmatic campaigns efforts with these opportunities.

If you are an e-commerce site owner or online merchant, you’ll observe that there there’s lot of exploring, browsing, clicking and product comparison happening, but do you find them actually translating into sales? Doesn’t that negate the very purpose of your running an e-store in the first place? Time to re-think your strategy? Where are the fault lines? However, identifying them is easier said than done. A proven technique adopted by marketers all over is personalization of content and segmentation of offers to cater to various customer strata.

From a data perspective, you will require Essential Insights, product data and historical purchase data. From a tool standpoint, even the most rudimentary of data analytics suite such as Google Analytics in conjunction with Essential Insights can do the trick.

The first step is to set up analytics on customer purchase data and product data. Start with a market basket analysis that will throw insights to the online merchant or site owner on the affinity of products such as what products can be sold with the corresponding product categories. This, in turn, will churn out a database or repository of products which can be utilized for upsell of cross-sell offers.

The next step is to analyse the insights. If the data shows that a visitor has been clicking on a particular product category, for example, Women's Fashion Sneakers, in a specific price range, say $25 to $50, then the data can be compared with the historical customer data, which may indicate that the customer is a habitual buyer of products belonging to Fashion Sneakers around the $40 price mark. It would also detail out the customer preference to last purchase data and product ratings.

Meanwhile, if you are using tools like Google Analytics or Adobe Target, you can create customer segments with customer IDs and leverage the product repository or database (using a customer ID) visits, the website may then display or list products related to a category that meets historical criteria, in addition to an upsell offer from their product sales database: a $70 Sneaker having a five-star product rating that has been doing good sales across the e-store.

It is 2018 and it’s time brands, retailers, online and e-commerce stores understand the dynamics of optimizing their online channels and start investing in their strengths. Advances in customer insights in the e-commerce space are constantly changing the way online store owners or merchants play the game. Increased deployment of SaaS solution in combination with merchant traffic data (Google Analytics, MixPanel, etc), sales data derived from multiple Payment Gateways (Paypal, PayU, PayTM and others) and shopping cart data from several eCommerce platforms (Magento, WooCommerce, Shopify, etc) has resulted in lot more detailed sales & traffic reports and performance insights such as user exit, retention, conversion, declined payments, charge-backs and range of other performance metrics.

Essential insights powers online merchants with valuable actionable data in a single data lake with a broader understanding of their customer, selling prospects, customer behaviour, affinity, product and their propensity.

Marketers can utilize Essential Merchant Insights to derive the right actionable insights at every point and connect the data points across a myriad of digital silos. Insights such as the user’s demographic info, browsing history, interests and purchase behaviour offer a clean display of the customer and his or her online activities. They can roll backwards in time to determine the very first of actions that initiated a user on their journey, or make use of predictive modelling to prefigure potential future actions.  

Ideally, while Essential Insights can track user behaviour online, it helps retailers to identify each customer as a unique customer, gathering the multiple data points to create an impactful ‘data-driven profile’ of each user. It offers marketers a 360 degree view over path-to-purchase activity, and thus brands can leverage the user journey to target customers at any stage of the funnel as required – from those carrying out top-of-funnel search pursuits, to those doing price comparisons or adding products to a shopping cart. The biggest takeaway of all is the strategic recommendations that help one improve sale performance and what is actually required so as to move the needle for your entire sales or marketing team.

When actionable data is actually distilled to a granular view over customer behaviour, not only will the business be able to find out and target new audiences, but also fully make out how and why they are truly converting as a result of marketing campaigns.