Customer Experience Analytics

Basic conversion funnel reports, user navigation or pathing reports are now outdated and least used methods to measure customer experience. 

Analyse the customer journey across devices and across channels before they converted. Understand which digital properties (website, mobile website or mobile app) are high performers and which are laggards in terms of customer experience. Which devices (tablets, mobiles etc), platforms (iOS, Andriod, windows), networks, cities the customers are on. Set up multi-channel funnel reports to understand the online sales cycle, understand how each channel in the funnel path contributed to conversion. 

Use pages, app screens, events, goals, e-commerce events and transactions to set up and analyze custom funnels. Where do the customers enter the journey and where do they drop off or loopback to previous stage.

Test multiple versions of landing pages, different ad content, different copies of articles (content marketing), different social media posts etc. using A/B or MVT tests before releasing the most effective content copy or landing page to each segment. 

Test multiple versions of goal funnel flows, understand and implement the funnels which have the least drop offs or loopbacks and highest goal completions. 

Target multiple versions of pages, promos, content across multiple customer segments to enable personalized customer experiences. 


Signature: Roopkumar T.V.

Application of Machine Learning algorithms in Digital Marketing

Some of the digital marketing challenges that can be addressed through machine learning algorithms include: 

• Helping digital media planners and buyers determine each media or ad position based on qualitative and quantitative research that is outside your own website or app. This expanded view may encourage media planners and buyers to focus on quality buying of of ad inventory reducing cost of untargeted or unqualified ad inventory.

• Enabling digital marketers to anticipate, identify and qualify audiences at the point of entry, and personalize content to maximize conversions or session outcomes. This will make content much more relevant and tailored to consumers. Also this personalization can be extended to multiple devices the audience uses. 

• Providing content feeds to digital users based on their interests, past interactions or other important factors.  Social media platforms have some limited capacity in prioritizing newsfeed content order based on viewing, timings, and likelihood to consume.  So many top tier online experiences train consumers to expect a custom experience. So not providing priority content will disappoint.

• Ranking visitors by value to the business. Not all traffic has equal value. Rapid website testing can be enabled and also personalization of page layouts, offers, messages, creative and content can be greatly improved by algorithms that have the means to assess the expected value of each visitor

Web UI Testing and Optimization

In the previous posts, I wrote about 

• Always delivering Relevant Landing Pages to Visitors coming from Search Engines and also about 
• How to optimize Conversion Ratio(%) of Website Conversion Funnels.

One important missing piece which was not discussed was Web UI Testing and Optimization. I had however mentioned about the necessity to extensively execute UI optimization tests in a previous post.


When do we need to do UI optimization for the Online Marketing Campaigns? 

1. To optimize page effectiveness of specific pages like Home page, Landing page, Sale page, Product Listings page etc.
2. Optimize Lead Generation Conversion Funnel performance
3. Optimize Cart-Checkout performance
4. Optimize effectiveness and usage of Web Forms.
5. Optimize eCommerce Purchase Funnels.
6. Optimize Search Effectiveness on the site
7. and many more

As seen there are many innumerable number of opportunities to optimize the performance of Web UI through continuous user testing. 


Why do we need to do UI optimization for the Online Marketing Campaigns? 

An optimized UI will benefit Online Marketing Campaigns on many dimensions like

• Increased Conversion Rate(%) of Clicks to Leads, Purchases etc.
• Increased traffic dispersion across the site. Improved Conversion(%) performance of Micro-conversions and mini-goals on the site.
• Improved customer engagement with the Web channel.
• Higher RPVs (Revenue per Visit) and higher RPUs(Revenue per Unique Visitor).
• Increased Share of Customer Wallet. Increase in Average Order Size, Product Attach Rates etc.
• Reduced Customer Churn Rate.
• Overall higher ROI from Marketing Campaigns due to increased Conversions.

The methodology for UI optimization testing, involves both Qualitative and Quantitative Analytics. 

More details on each of above methodologies for executing UI Optimization Testing, will be discussed in future posts.

1 Big Data Mining for UI Optimization Testing involves generating insights on the user experiences, by data mining of Call Center Transcripts, Email Messages, Social Media Messages etc. using Big Data Analytics platforms.

2 Design of Experiments for UI Optimization Testing is a Quantitative technique for optimizing UI, by executing A/B Tests or Multi-Variate Tests on 2 or more recipes of the UI. 


Signature: Roopkumar T.V.