With high customer expectations, the retail industry is on the edge to deliver seamless shopping experiences that stand out. With that in mind, Adobe Analytics empowers retailers to be more creative in gathering and analyzing data to gain in-depth insights into consumer behavior. However, simply implementing Adobe Analytics to your website won’t deliver results. You must make the platform robust via high-end customizations to utilize its capabilities fully.
In this blog, we will understand what challenges retailers face while implementing data analytics in their business and what are the Adobe Analytics implementation best practices.
What challenges does the retail industry face?
The retail industry is quickly adopting data-centric technology to increase sales, leveraging massive data across its supply chain and at diverse customer touchpoints. Here are a few challenges retailers face before implementing analytics:
- Businesses need data that provides more customized information to gain insights, segment customers, and deliver relevant marketing messages. But disparate data from multiple sources often results in profiles too segmented to be actionable.
- Most companies know the importance of data security, but many ignore it due to the complexity it creates. With bulk data gathering in the retail industry, the lack of big data security protocols results in internal and external risks affecting customer loyalty.
- Organizations need data from all the touchpoints to manage stock reliably and support marketing and sales teams in demand forecasting. Enterprises find this challenging to collect data from individual stores and online stores. Hence, Adobe Analytics tool is required for measuring valuable data.
- Retailers reach customers online or offline both ways, which makes customer experience challenging. That’s why providing customers with a smooth experience on the website becomes a priority. This is only possible when visitor tracking, mapping user behavior, measuring the impact of landing pages and banners, etc., come in handy to let users find information a lot faster.
Adobe Analytics best practices for retail
Let’s discuss Adobe Analytics implementation best practices that are essential for the retail industry to make customer tracking smoother:
#1. Merchandising variables
One of the most complex best practices of Adobe Analytics is eVars (merchandising variables). Adobe Analytics collects data in multiple ways, which can be used to gain insights. Merchandising variables allow you to tie the value of a variable to a specific product for a particular event. It can help you to find :
- How are visitors finding the products with the highest margins
- Are we getting value from recommendations or a live search
- Which products have lost the most revenue due to discounts
#Product String: Adobe Analytics Product String Builder extension automatically sets the products variable for you by looping through your data layer, grabbing all the product-related data, and formatting it in the proper syntax.
There are two types of eVars:
- Product Syntax: It is the standard approach for tracking and reporting in Adobe Analytics for eCommerce tracking and reporting. It stores contextual information about products like color, size, name, quantity, shipping, discounts, price, etc. You can choose product syntax when merchandising value is available at the same time.
- Conversion Syntax: It allows you to set a value other than the product string. You need to choose conversion syntax when the attributes you want to bind are not necessarily available in the same hit as the product you want to bind them to.
#2. Event serialization
Sometimes data does not match in back-end systems, be it purchases, submissions, checkouts, add to cart, or any other conversion event. It works by combining each instance of an event with a unique ID. Adobe Analytics features eliminates double counting. Retailers can flexibly align various systems by successfully implementing event serialization analytics.
#3. Segmentation
Adobe Analytics lets you create, manage, share, and apply influential, focused audience segments to reports along with other Adobe Experience Cloud tools. Segments give better audience insights by following values:
- Visitors-based on attributes: browser, device, number of visits, country, gender
- Visitors-based on interactions: campaigns, keyword search, search engine
- Visitors-based on exits and entries: social media, landing page, referring domain
- Visitors-based on custom variables: field, defined categories, customer ID
Adobe Analytics segmentation lets you identify patterns of consumer spending and associated behavior.
#4. Adobe Launch
Launch makes integrating easier with Adobe Analytics to Adobe Experience Platform, Adobe Target, and Adobe Audience Management. You can connect Adobe Launch with multiple technologies and turn data into action so you can deliver powerful, memorable experiences. Adobe’s current method is through tags in the Adobe Experience platform. Tags in Adobe Experience Platform is a tag management solution that lets you deploy analytics code alongside other tagging requirements.
#5. Set up alerts
Adobe Analytics tool lets you create and manage alerts to track and monitor data 24/7. Retailers can monitor data anomalies and maintain data integrity.
#6. Create calculated metrics
Calculated metric tools in Adobe Analytics offer a highly flexible way of building and managing metrics. They allow you, as marketers, product managers, and analysts, to ask questions about the data without changing your analytics implementation. Conversion and bounce rate metrics are the two most important calculated metrics in digital analytics for retailers. But with huge audience segmentation, retailers need to apply additional calculated metrics to enrich the analysis.
| Calculated metric | Why should retailers implement the metric? |
|---|---|
| Missed revenue | Retailers can calculate lost revenue if a customer chooses not to buy a product during checkout. |
| Checkout abandonment rate | To keep track of the percentage of customers that are leaving checkout after initiating the checkout process. Makes you understand the checkout flow. |
| Repeat purchase rate | For measuring the proportion of customers that make more than one purchase. Helps in understanding customer loyalty. |
| Subscription rate | Tracking on how many unknown visitors turned into potential customers. If the visitors give any information like email address, they can be counted in funnel prospects. |
| Revenue/ Visitor | Measure site traffic with different dimensions. |
| Add to cart rate | Retailers can measure the percentage of visitors who add products to their cart during a single session and compare it across different products. |
#7. Import product costs
Retailers must analyze which products are earning the most revenue to upscale the product performance. Adobe Analytics has the feature of bringing product costs into the platform to identify your most profitable products.
#8. Advertising analytics
Advertising Analytics lets retailers see all google and bing Paid Search data side by side within Adobe Analytics. By bringing the data together of these search engines in Adobe Analytics, you can analyze that same data leveraging Advertising Analytics. The integration of Advertising and Adobe Analytics will enable you to analyze and report on metrics like impressions, clicks, costs, and quality scores across dimensions like campaign, Ad group, keywords, etc.
#9. Data sources
In Adobe Analytics, you can upload ad campaign data and process it for dimensions and metrics, just like Advertising Analytics KPIs.
#10. Customize calendar
The retail calendar 4-5-4 is a guide for retailers that ensures sales compatibility between years by dividing the year into months based on 4 weeks, 5 weeks, and 4 weeks format. You can customize the calendar as per your business needs.
What are the data and segments across the Adobe Experience Cloud?
Adobe Analytics plays an important role in delivering data-driven decisions while integrating with other Adobe Experience Cloud solutions:
#1.Adobe Target
Adobe Target is a personalization tool where users can set up tests like A/B and multivariate tests and offer personalization experiences to end users. By integrating Adobe Analytics with Adobe Target, retailers can centralize data, making data analysis simple and efficient. With the data sent to Adobe Analytics via Adobe Target, all variables/metrics can be used to further explore the targeted users and gain in-depth insights. To measure the success of the target activity, use the clicks on the call-to-action and important milestones later in the funnels, such as actual conversion.
#2.Adobe Audience Manager
Adobe Audience Manager is a powerful data management platform that can help retailers to build unique audience profiles by integrating with Adobe Analytics. Retailers can incorporate data such as demographic, psychographic, CRM data, and advertising information in the Audience Manager to target unique segments and send personalized messages across multiple touchpoints.
#3.Adobe Campaign
Integration of Adobe Campaign and Adobe Analytics allows you to understand the success of your email campaigns directly from the familiar Adobe Analytics interface. You can easily analyze your desired email KPIs like decisions, opens, and clicks directly in the Adobe Analytics workspace. Retailers can also use the behavioral data from Adobe Analytics to trigger a tailored email in near-real time. You can send personalized messages to prospects who retailers have lost in the checkout process and reduce cart abandonment.
#4.Adobe Experience Platform
Adobe Experience Platform allows retailers to ingest Adobe Analytics data through the Analytics Source Connector. It requires processing rules like segmentation and visitor identification for mapping each Analytics variable.
#5.Adobe Commerce
Adobe Commerce and Adobe Analytics integration enables you to bring together the end-to-end customer journey focus of Adobe Analytics and the eCommerce platform. This lets you get a complete picture of your store’s overall performance.
Implement Adobe Analytics for your retail business with a trusted partner
Adobe Analytics implementation best practices for your retail business helps deliver one-on-one digital experiences across several devices. With Adobe Analytics, you invoke the power of data analytics and powerful reporting to optimize your campaigns for maximum performance and sale. If you need assistance with Adobe Analytics implementation for segmenting, identifying profitable products, tracking customer journeys, etc., you can connect with our certified experts to explore more of its business-driven features.
