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New Report from Acxiom Evaluates the Effectiveness of Marketing Technology in the Highly-Competitive Insurance Industry



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Senior Industry Leaders Understand the Power of Personalization for
Customer Growth and Retention but are Challenged with Creating Accurate
Data Foundations

the data and technology foundation for the world’s best marketers, today
at Dig|In 2019, released a new report in partnership with
SourceMedia Research. The study explores the top martech issues facing
senior leaders at P&C (Property & Casualty), life and multi-line
insurance companies. Despite significant investments being made in the
martech space, insurance carriers are struggling to get value out of
their investments. The joint report, ‘Marketing Transformation for
Insurance – A Study of MarTech Through the Eyes of Insurance Leaders,’
unveiled top-tier and mid-tier carrier strategies and challenges in
maximizing the value of their martech investments, influenced by
increased volumes of prospect and customer data from various channels.

“The rapid proliferation of channels, devices and data sources has
impacted the complexity of identity resolution strategies. This, in
turn, increases the risk of brand loyalty erosion as competition soars
in this transformative climate,” said Clark Wooten, group vice president
of insurance services at Acxiom. “Customers expect carriers to deliver a
seamless and highly personalized experience, but organizational and
industry obstacles, including data silos and evolving data privacy
policies, can create barriers between the expectations of customers and
the experiences delivered by insurers.”

Key Findings:

  • Twenty-three percent of insurance executives indicated that enhanced
    customer experience is their primary indicator of marketing success in
  • Thirty-six percent of executives cited data quality and accuracy as
    their biggest obstacle to being able to obtain a 360-degree view of
    the customer, curate actionable insights, assign accurate marketing
    attribution and measurement, and prove ROI
  • Nearly three-fourths of insurers are currently using between five to
    14 martech solutions— clear evidence of the data fragmentation
    challenge within insurance organizations
  • Nearly thirty-five percent of executives did not understand the
    martech solutions they were developing or purchasing, finding the
    tasks of achieving data quality/accuracy, marketing ROI, removing data
    silos and managing data governance very challenging
  • Customer acquisition and retention (66 percent), personalization (60
    percent), and increased competitiveness (56 percent) were ranked by
    executives as the most important martech investments in the next 12

The study also found that seventy-six percent of customers said they
were willing to take their business elsewhere if they weren’t getting a
highly personalized experience, and fifty-one percent said most brands
fell short of delivering a great customer experience. A Forrester report
in 2018 had similar findings. Data from Forrester’s CX Index proves that
when customers have a better experience, their intentions to stay with a
brand, buy more from that brand, and recommend that brand all increase.
But great customer experience in auto and home insurance is still rare.
That means that there is huge financial upside for insurers that
transform their customer experience.1 But simply
understanding the importance of making customer experiences better and
bringing together various martech tools designed to improve customer
experience are not leading to the success insurance marketers hoped to
achieve. The reason is that martech alone cannot solve the customer
experience problem.

“There is an overwhelming disconnect between results versus expectations
of the martech solutions insurance executives have purchased,” said
Jennifer Liptow, director of research operations at SourceMedia
Research. “Carriers must take a step back in order to get the data
foundation right, ensuring accuracy and compliance, in order to
effectively target customers and clearly differentiate their value
propositions among competitors.”

“The report clearly demonstrates that connecting the martech platforms
into what Acxiom terms a unified data layer or framework is much harder
than carriers realize. Many are trying to do this in-house but struggle
with integrations due to data challenges, lack of expertise and internal
resource constraints,” said Karen Imbrogno, senior insurance industry
strategist at Acxiom. “The majority of carriers are placing primary
focus on enhancing the customer experience yet struggle to measure
success with multiple projects continuously in play. The only way one
can measure accurately is by bringing all the data together — online,
offline, first-party, second-party and third-party data—into an
integrated framework.”

Findings from the report, which was conducted in 2018, are a telling
indicator of insurance executives’ priorities, with seventy-eight
percent of respondents stating that they are interested in implementing
a unified data framework solution to optimize their martech investments.
Partnership is key to uniting martech ecosystems at the data layer.
Since integrating marketing data and platforms is not a core part of an
insurer’s business, it is essential for them to work with an expert
partner who has a proven way to increase ROI and improve the customer

“Successful marketing depends on connected data at the foundational
layer,” added Wooten. “With a strong focus on creating a connected
ecosystem of marketing and advertising data services and technologies,
insurance companies will be able to create a single 360-degree view of
their customers while improving their ability to acquire, engage, and
retain customers, all of which is critical to proving ROI and maximizing

The report leveraged quantitative and qualitative interviews of 106
respondents at the director level or higher at top-tier and mid-tier
insurance carriers. To download the full report and learn more about
marketing transformation of the insurance industry, click here.

About Acxiom

Acxiom provides the data and technology foundation for the world’s best
marketers. We enable people-based marketing everywhere through a simple,
open approach to connecting systems and data that drives seamless
customer experiences and higher ROI. A leader in identity and ethical
data use
for nearly 50 years, Acxiom helps thousands of clients and
partners around the globe work together to create a world where all
marketing is relevant. Acxiom is a registered trademark of Acxiom LLC.
For more information, visit

About SourceMedia Research

SourceMedia Research is a full-service B2B market research service that
draws upon SourceMedia’s market expertise and proprietary database of
engaged executives to develop information and insights for clients.
SourceMedia Research provides research solutions for marketers, agencies
and others targeting sectors such as banking, payments, mortgage,
accounting, employee benefits and wealth management.

1 “The US Auto and Home Insurers Customer Experience Index, 2018:
How US Auto and Home Insurers Earn Loyalty with The Quality of Their
Experience,” by Ellen Carney, Faith Adams, August Du Pont, June 20,
2018, Forrester.


Sherry Hamilton
Director, Communications


Strainprint™ Technologies Welcomes Organic Medical Cannabis Producer to Growing List of Subscribers



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Strainprint™ Technologies Ltd, the leader in cannabis data and analytics is pleased to expand their nation-wide coverage with the addition of Stewart Farms.

Stewart Farms is a late-stage applicant headquartered in Alberta that is building a 100,000 sq. ft. vertical aquaponics farm in Saint StephensNew Brunswick. They will be utilizing automation, vertical farming, and land-based aquaculture to produce medical grade organic cannabis for both recreational and medical markets in Canada. All of their products will be free of herbicides, pesticides and synthetic nutrients. At full capacity, they will reach more than 10,000 kgs per year of organically farmed cannabis and more than 200,000 kgs of organic tilapia.

Stewart Farms’ long term vision is to deliver tools and products to support  future customers and patients during their health and wellness journeys. “Through our partnership with Strainprint we gain direct access to their incomparable data and analytics tools. This will aid us in educating a wider audience on the medical benefits and best practices of cannabis-based medicine,” said Tanner Stewart, Co-founder & CEO of Stewart Farms. “We know our customers are looking to consume more than dried cannabis. We know Canadians of all legal ages are trying to sort through their personal engagement with cannabis as a medicine. What we want to know, on an ongoing basis, is what is and is not working for people. Strainprint’s patient-led data services will give us the insight needed to create custom products and further understand the benefits of our existing products. Finally, our goal is to partner with companies and teams that truly have people’s best interest at heart. Caring about a patient’s success is what makes up the core of the Strainprint team. We couldn’t be happier to move forward with them at our side.”

Stewart Farms will access the Strainprint Analytics web platform, the most sophisticated cannabis analytics platform available to improve product development. Strainprint Analytics is built on top of the largest and most granular scientific data set of its kind in the world, with more than 1.3 million anonymized, patient reported medical cannabis outcomes and more than 65 million data points on strain efficacy.

“We’re thrilled to provide our real-time, crowd sourced data to an environmentally conscious company that uses innovative, cutting edge farming technology to produce top-tier medical cannabis,” said Strainprint CEO, Andrew Muroff. “Our organizations are equally committed to improving lives using cannabis therapy, and our shared core motivation is to provide guidance and support to help cannabis patients achieve their health goals.”


SOURCE Strainprint Technologies Ltd.

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Field Trip Ventures Inc. Retains KCSA Strategic Communications as Public Relations Counsel



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Greenery Map, the world’s first and only cannabis search engine to allow users to search for cannabis products based on their desired mood, medicinal use, and method of consumption, is now offering users – both businesses and consumers – the opportunity to register and connect to the app in an entirely mobile way. Previously, businesses were required to access from a desktop in order to manage accounts and connect to the inventory API system, but that road block has been removed, allowing for an entirely mobile experience through the Greenery Map app.

App users turn to Greenery Map to help them decide on the strain of Cannabis and product that is right for them depending on their desired mood or medicinal effect. Following the matching, consumers are given a detailed history and description of the strain so that they can make educated purchases, cutting down on time that budtenders need to spend with patrons and speeding up the purchase process. Consumers can then see all of the ways to purchase said product, including the nearby dispensaries that have it in stock, online options, and even delivery options through the app. Greenery Map fully integrates with a dispensary’s inventory API system to update in real-time and give consumers real-time information on dispensary stock for the item they are looking for. The Greenery Map system also provides cannabis businesses in both the B2B and B2C sectors a private database to share and sell information and products. For Cannabis businesses, Greenery Map also offers the opportunity to open bank and merchant accounts through their partnership with PayHouse Consulting Group.


SOURCE Greenery Map

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WeBank, IBM and Other Organizations Jointly Held the 1st International Workshop on Federated Machine Learning in conjunction with IJCAI 2019



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Once a concept, AI is now ushering in a key stage of application. What’s the solution to the data silos among businesses? Given the enhanced regulation on data at home and abroad, what’s the solution to data privacy and security concerns? What’s the status quo of Federated Machine Learning and how to establish an ecosystem for FML in the future?

WeBank, IBM and other organizations jointly held the 1st International Workshop on Federated Machine Learning for User Privacy and Data Confidentiality (FML’19) in conjunction with the 28th International Joint Conference on Artificial Intelligence (IJCAI-19) on Aug. 12, 2019, to further discussion on these issues.

President of IJCAI, Chair of FML Steering Committee, Chief AI Officer of WeBank Professor Qiang Yang delivered opening remarks at the workshop. Dr. Shahrokh Daijavad from IBM and Dr. Jakub Konečný from Google presented keynote addresses. In the panel discussion, top scholars from WeBank, Bar-Ilan University, IBM, Squirrel AI, Google, Huawei, Clustar, Sinovation Ventures and many other renowned enterprises and universities shared and discussed their findings and experience in FML as an emerging AI technology.

This workshop received 40 papers, of which 12 were presented during the workshop, 19 presented via poster. Awards include Best Theory Paper Award, Best Application Paper Award, Best Student Paper Award, Best Presentation Award. Selected high quality papers will be invited for publication in a special issue in the IEEE Intelligent Systems journal. All these attracted numerous scholars to engage in discussions and join efforts for building the FML ecosystem.

Experts from IBM and Google Share Groundbreaking Findings with a Focus on the Theory and Application of FML

Privacy and security are becoming a key concern in our digital age. On 25th May last year, the implementation of General Data Protection Regulation (GDPR) by the EU, the toughest Act on data privacy protection, stressed that user data collection must be open and transparent. A series of laws and regulations from China and overseas also pose new challenges to the traditional way of handling data and model for cooperation. Seeking ways for AI to adapt to this new reality became top priority, a demand that led to this workshop on FML.

A wealth of solutions and breakthroughs were shared by Dr. Shahrokh Daijavad from IBM and Dr. Jakub Konečný from Google in their speech on FML.

Besides how FML can help tackle challenges in the business world, Dr. Shahrokh Daijavad also shared the concept of Fusion AI, which means to train models on widely distributed data sets, but fuse them to produce one equivalent to what centralized training would yield. “Unlike traditional machine learning, in Fusion AI, model parameters are shared and data is not transferred, which makes Fusion AI model better than models that moving data centrally.” Given the widely distributed data, the development of Fusion AI and FML became ever important and imminent.

“FML enables machine learning engineers and data scientists to work productively with decentralized data with privacy by default,” said Dr. Jakub Konečný from Google. He also shared with us how FML works and its use cases at Google. In the case of Gboard, as on-device data is privacy sensitive or large or is more relevant than server-side proxy data, and labels can be inferred naturally via user interaction, the application of Federated RNN compared to prior n-gram model can increase the accuracy of next-word prediction by 24%, and the click rate of prediction strip by 10%.

Major Figure Panelists Discuss the Way Ahead for FML

The moderator of the panel discussion, AI Principal Scientist of WeBank Dr. Lixin Fan joined panelists including Professor Benny Pinkas from Bar-Ilan University, Dr. Shahrokh Daijavad of IBM Academy of Technology, Chief Architect of Squirrel AI Dr. Richard Tong, Research Scientist of Google Dr. Jakub Konečný, Dr. Baofeng Zhang from CTO Office of CBG Software in Huawei, Executive VP of Clustar Dr. Junxue Zhang, VP of AI Institute in Sinovation Ventures Dr. Ji Feng and other experts in a host of in-depth exchanges with attendees, to shed light on the way ahead for FML.

Experts shared thoughts in the panel discussion on questions including but not limited to: How to meet the security and compliance requirements? Is there a way to extend the value of data while observing user privacy and data security? Given the classic trade-off between data regulation and development of AI, how to achieve the long-term goal of establishing a stable and win-win business ecosystem?

List of Award-Winners

Best Theory Paper Award, Best Application Paper Award, Best Student Paper Award and Best Presentation Award selected by all attendees were announced at the closing of the workshop.

Best Theory Paper Award: 
Preserving User Privacy for Machine Learning: Local Differential Privacy or Federated Machine Learning? By Huadi Zheng, Haibo Hu & Ziyang Han;

Best Application Paper Award: 
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare. By Yiqiang ChenJindong WangChaohui YuWen Gao & Xin Qin;

Best Student Paper Award: 
Quantifying the Performance of Federated Transfer Learning. By Qinghe JingWeiyan Wang, Junxue Zhang, Han Tian & Kai Chen;

Best Presentation Award: 
Federated Generative Privacy. By Aleksei Triastcyn and Boi Faltings.

President of IJCAI, Chief AI Officer of WeBank Professor Qiang Yang, Chief Architect of Squirrel AI Dr. Richard TongandVP of AI Institute in Sinovation Ventures Dr. Ji Feng presented the awards.

“The mission of this International Federated Machine Learning Workshop is to facilitate further understanding in the academia, business community as well as legal and regulatory institutions by promoting the establishment of FML ecosystem in the hope that more businesses will join and build a platform for students aspired to work in FML to find research teams that suit them,” said Professor Qiang Yang.

Held Aug. 10-16, 2019 in Macao, China, IJCAI-19 is one of the leading International Academic Conference on AI, attracting over 3000 AI research personnel and experts. The 1st International Workshop on Federated Machine Learning (FML’19) was a highlight for experts joining this event. Visionaries in the academia and industrial sector expressed the willingness to be part of the effort for academic research, application of FML in the future, and the development and boom of AI ecosystem.

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