data analytics

“Bridging Data Science and Research Insights” – MediaScience

The session is designed to help empower researchers by better acquainting them with data science opportunities.  At the same time, data scientists lacking media experience are being thrown into the deep end with demands for answers to questions the context of which they don’t fully understand. 

 The session helps educate them on the benefits of collaboration.  Bridging the gap between these communities will be critical to both groups going forward.

For more information visit Audience Measurement

 

 

From AdAge: Cruz Loss Shows Data Can’t Win ‘Em All

After Ted Cruz won the Iowa Caucus, reports suggested his campaign’s sophisticated use of data and analytics to target voters with messages customized to their psychological proclivities had a lot to do with it. A few months later the Texas Senator left the race. 

Donald Trump captivated primary voters with simple mass-marketed brand messaging through earned media rather than spending on precisely-targeted digital and TV media. This will have many pundits wondering what it all means for the use of data in politics.

Chris Wilson, director of research & analytics for the Cruz campaign said that the Senator survived amid a flood of 17 candidates. “So, no, it’s not magic. But a sophisticated data operation sure can make things easier along the way.”

See more >> http://adage.com/article/campaign-trail/cruz-loss-shows-data-win-em/303879/

Analytics-The Benefits and the Challenges

Who Will Be Increasing Their Marketing Analytics Spending by 66%

The “CMO Survey Report: Highlights and Insights,” August 2015 survey by Christine Moorman and sponsored by McKinsey & Company, American Marketing Association, and The Fuqua School of Business at Duke University, analyzes spending on marketing analytics by firm and industry characteristics.  The survey shows how companies use marketing analytics to drive decisions, how that use is changing, and other metrics related to marketing analytics.  This survey also analyzes other issues of concern to CMOs.  TAGS: CMOs, marketing analytics.  See more . . . Source: http://cmosurvey.org/files/2015/09/The_CMO_Survey-Highlights_and_Insights-Aug-2015.pdf

How to Deliver Positive ROI by Using Predictive Marketing

This Forbes Insights report, “The Predictive Journey,” undertaken in association with Lattice Engines, is based on their 2015 Survey on Predictive Marketing Strategies.  According to this report, mature users of predictive analytics technology report tangible gains to their bottom lines.  Eighty-six percent of marketing executives who have been overseeing predictive marketing for at least two years report an increased return on investments as a result of their predictive marketing. The report also reports on the business value gained from predictive marketing, predictive marketing success metrics, and other key findings. TAG: predictive analytics.  See more . . . Source: http://images.forbes.com/forbesinsights/StudyPDFs/Lattice-ThePredictiveJourney-REPORT.pdf

CPG Firms Too Slowly Becoming Analytics-Driven Organizations?

This research report by Accenture, “CPG Firms Slowly Evolving to Analytics-Driven Organizations,” explores how CPG companies are structuring analytics-driven organizations, and how they are “infusing” analytics into the decision-making processes.  While some of the largest CPG companies (revenue more than $5 billion) have analytics well integrated into core processes, this report concludes that most CPG companies are in the early stage of their analytics journey.  However, companies are committing resources to analytics, and this evolution is accelerating. The report also addresses the barriers that prevent CPG companies from realizing value from analytics, such as the challenges of hiring talent with advanced analytics expertise.  TAG: CPG.  See more . . . Source:  https://www.accenture.com/ae-en/~/media/Accenture/Conversion-Assets/DotCom/Documents/Global/PDF/Industries_2/Accenture-CPG-Firms-Slowly-Evolving-to-Analytics-Driven-Organizations.pdf

Will Your Data Analytic Efforts Fail?

David Court, a Director in McKinsey’s Dallas Office, analyzes the challenges faced by companies undergoing the transformation necessary to realize the large-scale benefits of data analytics in this McKinsey Quarterly article, “Getting Big Impact From Big Data.” This article provides some of the reasons why data analytics efforts fail to achieve the scale necessary, as well as analyzing the new tools and approaches that are available.  Among the actions recommended are a focus on change management, a redesign of workflows and jobs, as well as a building a foundation of analytics within the corporate culture.  TAG: data analytics.  See more . . . Source:  http://www.mckinsey.com/insights/business_technology/getting_big_impact_from_big_data

Report by White Ops and ANA – “Did Ad Fraud Increase or Decrease Y-O-Y?”

Suzanne Vranica, writing for The Wall Street Journal, discusses the study done by the Association of National Advertisers (ANA) and White Ops Inc. on bot fraud in this article, “Bogus Web Traffic Continues to Plague the Ad Business.” The 2015 study found that between 3% and 37% of the ad impressions of advertisers participating in this study were created by bots. Bot traffic ranged from 2% to 22% in the 2014 study. The article analyzes the red flags related to ad fraud. TAG: bot fraud.  See more . . . Source:  http://www.wsj.com/articles/bogus-web-traffic-continues-to-plague-the-ad-business-1453204801

Top Trends for Mobile Advertising and Data Science in 2016

Lauren Moores presents the five top trends for mobile and data science in 2016 in this Advertising Age article. Marketers will begin adopting beacon proximity signals, mobile audience modeling and prospecting will get more sophisticated, advertisers will dig into physical and emotional signals from wearables, creative agencies will turn to data science to optimize campaigns, and cross-device marketing will become even more prevalent.

Moores points out that mobile is a way of living and a vehicle for content and communications.  In 2016, the distinction between digital and linear channels will begin to blur, and marketers will combine behavioral and geolocation signals to uncover new customers.  In addition, there is strong potential for campaign and audience optimization as a result of mobile data.

See all 5 Cups articles.

 

 

The Corporate Cost of Bad Prospect Data

The high cost of bad prospect data is analyzed by Henry Schuck in this MarketingProfs article.  A sales department can lose approximately 550 hours and $32,000 for every sales rep using bad prospect data.

Bad data includes incorrect phone numbers, outdated physical and email addresses, incorrect titles or job functions and misspellings.  Sources of bad data include data input by prospects and data from the Internet.

Schuck points out that bad data has both soft and hard costs:

Soft costs include impact on morale caused by lower salaries for sales reps who depend on profitable leads.

Hard costs include missed sales opportunities for the organization.

Time wasted by the sales and marketing departments is also a cost to be considered.

The author recommends that marketers dedicate a team to more frequent data management or invest in sales intelligence solutions.

 

See all 5 Cups articles.

For more on this topic, check out the Marketing Tab in Morning Coffee.

 

 

We Need a Bigger Toolbox

A report from the IAB and the Winterberry Group reveals that enterprise marketers use on average over a dozen distinct ad/marketing data toolsets, with close to 10% using more than 30 tools. Tools were mainly used by organizations’ digital marketing, analytics, media buying, and CRM teams. Read more »