Our enterprise clients always ask an important question at the beginning of every financial year: how should we smartly plan our upcoming financial year from a digital analytics perspective?  

If we go a little bit deeper into this question, what they are actually trying to ask would include:

  1. What kind of initiatives they should run in the upcoming financial year?
  2. What kind of short-term and long-term goals should they have?
  3. What initiatives will drive better engagement and conversion rates?
  4. What kind of budget do they need to set aside to pursue these initiatives?
  5. How should they go about prioritizing these initiatives?

In response to these questions, we do a comprehensive exercise of creating a highly customized Digital Analytics Roadmap for their business in collaboration with their Marketing, Analytics, and IT Teams. Our roadmap not only respects their current data infrastructure investment, but also takes into consideration their last year initiatives, the number of accomplishments they had on a monthly and quarterly basis, and most importantly, the type of quarterly and annual goals they have set aside for the upcoming financial year.

At the beginning of this financial year, we did this exercise for three enterprise clients and educated them about the eight key initiatives they should plan out for 2016. For the interest of our enterprise blog readers, we are demystifying those eight initiatives here:

  1. Migrate To Enterprise Tag Management System
  2. Build Marketing Data Mart For Visualization And Advanced Analysis
  3. Create Fusion Dashboards
  4. Take Test-Driven Optimization Initiatives
  5. Do Advanced Analysis On Click-Stream Data
  6. Conduct Mobile App Tracking And Cross-Device Analysis
  7. Invest In Data Management Platform
  8. Perform Data Governance

There is a significant percentage of online businesses in our digital ecosystem who are still relying on the traditional ways of tagging their pages. They are heavily dependent on the DOM objects instead of setting up a Universal Data Layer and deploying their analytics and marketing pixels via enterprise Tag Management System. If you are among those online businesses who are still following the on-page tagging approach and struggling with frequent data quality and integrity issues, we would highly recommend investing in this area as a top priority in this financial year. Migrating to an enterprise tag management solution is going to be the foundational initiative for other interesting things you are going to pursue in this financial year. Our top two picks for the Tag Management System would be Tealium and Google Tag Manager.

Fusion Dashboards is one of our key value offerings for enterprises as well as for small and mid-sized media agencies. This is one of those initiatives that we highly recommend to our clients as a part of their Digital Analytics Roadmap every year because it touches three main aspects of a great dashboard:

  1. Operational/good to know measures
  2. Actionable insights for the marketers and business stakeholders
  3. Stats has driven recommendations

To get a Fusion Dashboard for your organization, you need to provide us with the following inputs:

  • What are the three main business questions you want to get answered?
  • Your channel(s) specific historical data (at least last 3 months). You can share this via Excel Data Extract or simply provide us with your API Token Key.
  • What tool or technology you want to leverage to build this dashboard? Our preferred tools are Tableau and Excel.

Take Test-Driven Optimization Initiatives

Both A/B and Multivariate testing are among the most discussed and appreciated topics in our industry but despite that they are not very well accepted and implemented by the enterprises due to the following factors:

  • Inadequate sample size
  • Challenges on the resource front especially on the creative side
  • Tough to justify the cost of the testing tools and the resulting ROI
  • Lack of in-house optimization experts who could run the show
  • The Past unsuccessful experiences
  • General misconception that testing delays the overall optimization tasks and often causes time and cost overruns.

At Nabler, we provide end-to-end testing and optimization service where we take the responsibility for the following activities and keep the barrier to entry extremely low:

  • Weekly and monthly insights
  • Finding opportunities for content, layout and workflow optimization
  • Building tests hypothesis
  • Creating test variations through our creative agency
  • Suck-up the cost for the testing tool
  • Assign a dedicated optimization manager who works closely with the client’s marketing and content team
  • Test setup and configuration
  • Test segments identification
  • Winner declaration
  • Crafting the targeting strategy

Do Advanced Analysis Of Clickstream Data

Clickstream data always poses a challenge for the analysts as it doesn’t usually fit the assumptions (normality, structure, etc.) that are the basis of the statistical tests, but there are few areas where these can be useful:

  • Finding local anomalies/small variations on the seasonal trend, which don’t extend beyond the usual range of values. The Anomaly Detection package in R uses Seasonal Hybrid ESD algorithm, which combines seasonal decomposition with robust statistical methods to identify local and global anomalies. It can be applied to both engagement and conversion measures like Page Views per Visit, Time Spent per Visit, Bounce Rate, Lead Conversion Rate, Transaction, etc.
  • Using Predictive Modeling technique, we can forecast the impact on the Lead Conversion Rate by region when the search and display spend was increased by a certain percentage.
  • Customized Lead Scoring models can be build using R by exporting the raw un-sampled clickstream data via Once the model is built, the score values can be imported as a custom dimension in Google Analytics and leveraged via Advanced Segments and Custom Reports.
  • Lifetime Value Analysis can be done using R by exporting the raw un-sampled clickstream data via BigQuery. Once the model is built, the Lifetime Revenue Contribution values can be imported as a custom dimension in Google Analytics and leveraged via Advanced Segments and Custom Reports.
  • Regression analysis can be performed on dimensions like Online Promotions/Offers, Home Page Offers, and Cross-Sell/Up-Sell Recommendations to gauge their impact on measures like Transactions, AOV, and Revenue Numbers.

 

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