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Behavioral Analytics

By Matteo Belardi

Introduction

Behavioral Analytics is a subset of business analytics that focuses on how and why users of eCommerce and retail platforms, web applications and gaming behave.

Matteo Belardi — Expert in Management and Analytics Advisor, PhD & MBA. Specialist in the creation and use ...

Added by Matteo Belardi: “4 Ways Behavioral Targeting Is Changing the Web

1 4 Ways Behavioral Targeting Is Changing the Web

The Digital Marketing Series is supported by HubSpot, which offers inbound marketing software that helps small and medium sized businesses get found on the Internet by the right prospects and converts more of them into leads and customers. Learn more.We've already seen signs of it - targeted ads on Facebook, suggested people to follow on Twitter, even Google Instant seems

Added by Matteo Belardi: “User behavioral analytics. Your audience is the lifeblood of your business, and knowing who they are and what they want is a key to success.

3 User behavior analytics

Added by Matteo Belardi: “Data analytics, a subset of big data, allows you to draw actionable data from data sets that seem to be unrelated and completely arbitrary. This slide deck give a short overview of behavioral analytics.

5 DEFINING BEHAVIORAL ANALYTICS

Added by Matteo Belardi: “ FAST COMPANY ARE USER BEHAVIOR ANALYTICS THE REAL PREDICTORS OF CUSTOMER ENGAGEMENT? By Shawn Graham, FastCompany When it comes to consumer insights, the rise of the social web has been both a blessing and a curse: a blessing because companies now have an unlimited amount of data about their customers at their fingertips; a curse because they have to figure out a way to sift through all of that data to figure out what’s meaningful and what isn’t. Every Facebook fan page, Twitter profile, and mobile app means that much more data about your customers. And if you’re going to win market share and better engage your customers, you’re going to have to look way beyond clicks and conversions. Social gaming startups figured it out early. Whether it’s because they we’re chocked full of deeply talented engineers who were able to interpret complex data or because of the hyper growth and hyper competition within the social gaming industry, companies like Zynga were able to rapidly interpret and develop meaningful insights from billions of data events each day. They used customer data to drive engagement, fuel product development, and improve the user experience. The rise of user behavior dynamics As more data became available, big brands started to realize they could leverage user behavior dynamics to target their marketing efforts in ways that wouldn’t have been possible even a year or two ago. "There is an immense amount of customer data flowing through the social web--orders of magnitude more than in the 'pre-social era' of the Internet," said Josh Williams, President and Chief Scientist at Analytics firm Kontagent. "By tapping into analytic platforms like Kontagent, businesses now have an unprecedented opportunity to deeply understand and optimize their customer economics. By pulling the very levers that drive effective user acquisition, engagement, retention, and monetization, we are enabling our customers to build stronger businesses by acting on real-time data insights that affect their bottom line." Take, for example NoWait, a Pittsburgh-based startup that created an app to simplify the process of waiting for a table at a restaurant. Instead of having to tote around one of those clunky pagers that typically only have a range of 50 feet in any direction, all you need to do is provide your cellphone number. When you’re table is ready, you get a text. Once you’re finished dining, you receive a text asking if you’d like to receive discount offerings from other local restaurants. But that’s only part of what makes their solution a game changer in the restaurant space. For the first time, restaurants will know who their patrons are, what time they come and go, which patrons come back the most frequently, who purchases more--and use all of that data to craft messaging that appeals specifically to each unique patron based on their unique usage. Understanding and engaging customers requires looking beyond traditional web analytics. To optimize and engage the end user experience across multiple touch points including the web, social sites, and mobile applications, companies must instead focus on user behavior dynamics to analyze and identify deep behavioral insights from their data.

6 Are User Behavior Analytics The Real Predictors Of Customer Engagement?

When it comes to consumer insights, the rise of the social web has been both a blessing and a curse: a blessing because companies now have an unlimited amount of data about their customers at their fingertips; a curse because they have to figure out a way to sift through all of that data to figure out what's meaningful and

Added by Matteo Belardi: “Behavioral Analytics to Foster Long Term Changes. The use of wearable technology allows to quickly collect behavioral patterns from users, analyze them and intervene in the environment. In this talk we explore the potential of this technology with the comoditization of sensors.

7 Behavioral Analytics to Foster Long Term Changes

Added by Matteo Belardi: “Behavioral Analytics & Cohort Analysis. Cohort analysis is a subset of behavioral analytics that takes the data from a given eCommerce platform, web application, or online game and rather than looking at all users as one unit, it breaks them into related groups for analysis. These related groups, or cohorts, usually share common characteristics or experiences within a defined timespan. Cohort analysis allows a company to see patterns across the lifecycle of a customer. By seeing these patterns of time, a company can adapt and tailor its service to those specific cohorts. Cohort analysis has come to describe specifically the analysis of cohorts in regards to big data and business analytics, while a cohort study is a more general umbrella term that describes a type of study in which data is broken down into similar groups.

8 What are cohorts: Cohort Analysis

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