Social Media & Web Analytics Innovation Summit 2014: Day 1 Highlights

Businesses now have more access to information on customer than ever before; the opportunity to provide real-time analysis of customer interactions is becoming increasingly important in identifying an advantage over competitors. The challenge remains to make use of this data to build and maintain a loyal client base.

Through investment in innovative web analytics practices and analysis of social media platforms, organizations are offered a unique opportunity to react to the data made available. To learn more about such opportunities, success stories, challenges and best practices, I recently attended the Social Media and Web Analytics Innovation Summit 2014 (May 1-2, 2014) at San Francisco, CA, organized by the Innovation Enterprise. The summit brought together industry leaders who have seen results from implementing an effective web analytics initiative to share their case studies and best practices. Illustrated intermittently with case studies, interactive panel sessions & deep dive discussions this summit offered solutions and insight from those working within the space.

It covered a wide variety of areas including measuring, evaluating & predicting the Social Consumer, Multi-Platform Consumer Engagement, Social Media ROI and Multi-variate consumer engagement and more. To help its readers succeed in their Analytics pursuits, KDnuggets provides concise summaries from selected talks at the summit. These concise, takeaway-oriented summaries are designed for both – people who attended the summit but would like to re-visit the key talks for a deeper understanding and people who could not attend the summit. As you go through it, for any session that you find interesting, check KDnuggets as we would soon publish exclusive interviews with some of these speakers.

Here are highlights from selected talks on day 1 (Thu, May 1):

Clifford Lyon, Head of Technology Recommender Systems at StubHub delivered the very first talk discussing about development of an Enterprise-Scale Recommender Solution. Organizational complexity is the biggest challenge as professionals from different domains such as science, engineering, business and product need to be brought together. A good solution will focus on organization by ensuring the fundamental function in each aspect first and continuously improving once effects on KPIs are established. The key prerequisites are source data, tracking system and testing system. In the execution phase technology, product and business professionals work together to understand the problem well and come up with best solution to make things work.

Choosing the right similarity metric plays a significant role in recommender systems. Product experts put recommendation in the user experience and figure out the channels to which recommendations can it be applied for example mobile, email, app, etc. Business experts should focus on KPIs to drive quality and just not quantity (by merely focusing on click rate). Concluding the talk, Cliff emphasized that the big challenge of organizational complexity can be solved by working on all aspects first at high-level and then improving iteratively through testing, acquiring more data, etc.

Marc Smith, Director, Social Media Research Foundation talked about “Charting Collections of Connections in Social Media”. Briefly describing Social Network Theory, he explained the various components of graphs relating to social context. Key metrics of measuring social network characteristics are centrality, cohesion, density and betweenness. He claimed that crowds matters the most and explained how connections between people in crowds clearly define sub-groups. Social Media is all about connections from people to people. Each event that occurs leaves behind a pattern, which can be analyzed and used to predict similar upcoming events.

As more social interactions move through, machine-readable data sets new insights and illustrations of human relationships and organizations become possible. But new forms of data require new tools to collect, analyze, and communicate insights. He introduced the NodeXL tool, and demonstrated how one could map and measure social connections using NodeXL. With the goal of making Social Network Analysis easier, NodeXL performs network analysis as per the data flow shown below. At the end, he displayed various visualizations of Twitter data for some popular hash tags using NodeXL.

See also KDD-2013 NodeXL Twitter Social Network and
KDnuggets Twitter Social Network, both created with NodeXL.

Adam Singer, Analytics Advocate, Google presented on “Metrics for the Mobile App Ecosystem”. With millions of apps available on Google Play store & iTunes App Store, the App Revenue is projected to be over 46 billion by 2016. Thus, it is high time for enterprises to start building their apps if they don’t have it yet. More than half of Americans now own a smartphone. Now users are more interested in documenting and sharing things on smartphones, which are empowering the users. He recommended monitoring metrics such as click to call, time spent browsing, etc.

Google Analytics is now switching from session-based world to user centric view. In its move from web analytics to digital analytics, Google has introduced some cool features including cross device tracking which allows tracking user’s actions over multiple devices (web, mobile, smart TV, etc.). Google’s Universal Analytics can also track native mobile apps provided it is connected to web. The mobile analytics have three focus areas: acquisition, engagement, and outcomes.

Krish Swamy, Director, Digital Analytics and Personalization at Capital One delivered a talk titled “Online Analytics: From Vanity to Actionability”. He commenced the talk stating the purpose of analytics as enabling smart decision, leading to "actionability". He then defined "actionability" as digital product improvements i.e. existing feature enhancements, adding new features, etc. He discussed how our thinking of the digital space has evolved, as now digital is a medium to engage and delight customers. So, the importance of customer engagement has been accentuated by recent consumer trends. Looking further deep, true engagement means users finding digital experience useful, usable and enjoyable. Krish presented a case study about his own company’s website. He concluded stating that there are five analytics steps to achieve actionable insights:

1. Identify tasks such as baseline analytics
2. Define relevant metrics for each task
3. De-average into segments of interest
4. Benchmark
5. Tie back to business outcomes

 
Next part: Highlights of talks on Day 2