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:
- What kind of initiatives they should run in the upcoming financial year?
- What kind of short-term and long-term goals should they have?
- What initiatives will drive better engagement and conversion rates?
- What kind of budget do they need to set aside to pursue these initiatives?
- 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:
- Migrate To Enterprise Tag Management System
- Build Marketing Data Mart For Visualization And Advanced Analysis
- Create Fusion Dashboards
- Take Test-Driven Optimization Initiatives
- Do Advanced Analysis On Click-Stream Data
- Conduct Mobile App Tracking And Cross-Device Analysis
- Invest In Data Management Platform
- Perform Data Governance
Migrate To Enterprise Tag Management System
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.
Build Marketing Data Mart For Visualization And Advanced Analysis
Last year we received various requests from mid-sized to large media agencies and enterprises about how they can achieve the cross-channel view of their data and build customized data visualizations using tools like Tableau and Qlikview. Besides this, they wanted to know how they can further enrich these visualizations by ingesting the output of their statistical models created with open source statistical packages like R and Python, and generate actionable insights and predictions for the business and marketing teams. If you are among those enterprises who are extremely passionate about cross-channel analysis, our data preparation platform can help you achieve that vision by building a customized Data Mart, which you can be leveraged for both, Data Visualization and Advanced Analysis.
Create Fusion Dashboards
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:
- Operational/good to know measures
- Actionable insights for the marketers and business stakeholders
- 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 InitiativesBoth 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.
Conduct Mobile App Tracking And Cross-Device Analysis
If you are among those online businesses who have still not invested in tracking their mobile websites and apps, then this is going to be a crucial year for your Marketing, Content and IT teams to act on because there are a lot of significant cross-device interactions happening in the digital ecosystem. Last year we observed that approximately 28-30% of the online transactions were influenced by cross-device activities. For some of our clients, we observed an equal split in the traffic across Desktop, M-site and Mobile App, however, the percentage of engagement and conversions were quite higher for mobile apps and desktop websites. The engagement level and retention rate for the App users is significantly higher as compared to Android Users. The Lifetime Value for the Organic and Email channel visitors is significantly higher as compared to Direct and Paid. The display has been a consistent under-performer.
Invest In Data Management Platform
In the last 18 months, we observed a large percentage of mid-sized to large online businesses invested either in a vendor-neutral Data Management Platform like Tealium or Ensighten, or locked themselves up with a cloud-based DMP platform like Adobe Audience or Oracle BlueKai. We are predicting a similar trend this year too and expecting a surge in this investment. Here are some tips for choosing a right DMP Solution for your organization:
- Whichever DMP solution you pick, it should not only allow you to leverage the FIRST PARTY COOKIE data coming from different devices (Desktop Website, Mobile Website, and Mobile App), but also allow you to enrich your audience profiles by stitching the Third Party Cookie data, even though the match rate would be less than 15%.
- The DMP solution should have outbound data connectors for exposing the audience profiles to the known DSPs and Ad Serving Platforms. If you go for Google Audience Center, it would have a seamless connection with DoubleClick Bid Manager.
- The DMP solution should allow you to export the audience profiles in your own cloud storage so that you could run statistical models on top of it.
- The DMP solution should allow you to expose the audience profiles to your DATA LAYER for personalizing the consumer experience on the website and mobile apps.
- The DMP solution should be able to handle and interpret the Mobile App traffic and provide a mechanism to stitch the Desktop and Mobile traffic. Most of the DMP solutions in the market don’t have better capabilities around Mobile space.
- The DMP solution should be fast in recommendations, should be scalable, and should have a robust platform.
Perform Data Governance
Data Governance is a known challenge for over a decade now, and we are really surprised that still a significant percentage of online businesses consider it either as a low priority item, or they just don’t know how to implement it across the organization. Considering the amount of evangelization that has happened in our ecosystem in last few years; we are predicting this initiative to be a key component of the Digital Analytics Roadmap in 2016, and we expect that more and more organizations would invest heavily in this space in order to maintain the quality and integrity of their digital data. To learn more about this topic and how Nabler can assist you in this regards, do check our recently published analytics recipe on DAA.
For the convenience of our enterprise readers, we have made an attempt to plot the above eight initiatives in a yearly roadmap broken down by quarters. We hope that it will resonate with your investment plans for 2016 and give you a direction on how to prioritize them based on your organizational needs.
To learn more about our Digital Analytics Roadmap service, do contact us.