Much criticism has been levied towards marketing-mix modeling recently. This article shows innovations and proposes solutions for reinventing this powerful marketing measurement tool
This is a case showing how Structural Equation Modeling (SEM0 can be applied to common consumer tracking surveys, media data, web traffic info.,and social media metrics to develop a mapping and quantification of the "customer journey" from awareness to purchase and brand loyalty.
Marketing ROI Measurement for RestaurantsMichael Wolfe
Case study of how a QSR restaurant used marketing ROI models to identify opportunities to expand growth of their business. In this case, showing how spending more on a new item launch will accelerate business growth.
Marketing ROI Measurement & Case Study for TelecomMichael Wolfe
Wireless Telecom is a complex category, with multiple ad messaging from ads for cellphones, cellphone plans and branded messages claiming network superiority. This is an actual case study that sorts all of this out and illustrates the power of marketing measurement and ROI assessment
A case study marketing mix model for major department store retailer. The. data source is credit-card transactions, segmented among Millennial (18-24), Gen XZ (25-54) and Boomer (55+)age groups. This measures short & long-term advertjsing plus the impact of media creative. The work examines and evaluates this retailer's "Millennial's only" media targeting strategy.
Innovations in marketing effectiveness measurement v.2Michael Wolfe
Demonstrates a comprehensive & holistic approach to marketing effectiveness modeling which includes measures of creative effectiveness, long-term ad effects, measuring marketing synergies and a unique approach to measuring the customer-brand experience using social media.
This is a case showing how Structural Equation Modeling (SEM0 can be applied to common consumer tracking surveys, media data, web traffic info.,and social media metrics to develop a mapping and quantification of the "customer journey" from awareness to purchase and brand loyalty.
Marketing ROI Measurement for RestaurantsMichael Wolfe
Case study of how a QSR restaurant used marketing ROI models to identify opportunities to expand growth of their business. In this case, showing how spending more on a new item launch will accelerate business growth.
Marketing ROI Measurement & Case Study for TelecomMichael Wolfe
Wireless Telecom is a complex category, with multiple ad messaging from ads for cellphones, cellphone plans and branded messages claiming network superiority. This is an actual case study that sorts all of this out and illustrates the power of marketing measurement and ROI assessment
A case study marketing mix model for major department store retailer. The. data source is credit-card transactions, segmented among Millennial (18-24), Gen XZ (25-54) and Boomer (55+)age groups. This measures short & long-term advertjsing plus the impact of media creative. The work examines and evaluates this retailer's "Millennial's only" media targeting strategy.
Innovations in marketing effectiveness measurement v.2Michael Wolfe
Demonstrates a comprehensive & holistic approach to marketing effectiveness modeling which includes measures of creative effectiveness, long-term ad effects, measuring marketing synergies and a unique approach to measuring the customer-brand experience using social media.
Innovations in marketing effectiveness measurement Michael Wolfe
A new and innovative approach in marketing ROI measurement. Goes beyond traditional marketing mix models by 1) developing long-term ad effects measurements, 2) measuring media message and creative, 3) quantifying the interactions or synergies across the marketing mix and 4) measuring the voice-of-the customer through social media
The Smart Cube | Marketing Mix Modeling: An Old Remedy for New IllsMelissa Luongo
Authors:
Ankit Abraham Sinha, Senior Analyst
Sidharth Sreekumar, Assistant Manager
What is Marketing Mix Modeling (MMM)?
MMM is the use of statistical analysis to estimate and predict the impact and effectiveness of media channels, price changes, promotions, and external factors on the sales volumes of a company. This helps demystify the relationship between a company’s marketing spend and its bottom line.
Measuring the Effectiveness of Marketing Spend Using MMM
Increasing Marketing Spend
As global ad spending increases, it is imperative for companies to ensure that they get the best bang for their buck. In this scenario, the need to measure the impact of various marketing media on sales and deploy marketing funds efficiently is even greater.
The Need to Measure the Impact of Marketing
According to an April 2014 study by VisionEdge Marketing and ITSMA, 85% of marketers polled were of the opinion that the pressure to measure the value and contribution of marketing is increasing. In addition, a May 2014 study by Ifbyphone states that 60% of marketing executives report marketing metrics to their business leadership teams at least on a monthly basis. This highlights the increasing emphasis being laid by business leaders on the need for regular and more accurate measurement of marketing metrics that highlight the impact of marketing spend on business performance.
Top 20 Reasons Why Agent-based Modeling is Disrupting Marketing MixThinkVine
Misallocated ad dollars may be costing brands more than 25 percent in lost sales. Based on an analysis of ThinkVine customers with average annual sales of more than $1 billion, we found that companies were spending too much or too little on specific media 85 percent of the time. By optimizing their marketing budgets, the companies added anywhere from 7 to 81 percent in additional revenue attributed to marketing activities – an average of 28 percent.
Don’t lose out on the additional sales your marketing could be driving. Brands have been relying too heavily on outdated, backward-looking marketing mix methods that leave money on the table.
Companies are now turning to agent-based modeling to make better strategic decisions that will deliver the results they need, and here is why.
Learn How a New Kind of Marketing Mix Modeling is Better for Media PlanningThinkVine
This presentation discusses the use of agent-based modeling and its proven advantages to media planners, including the abilities to create effective media plans based on consumer differences, accurately attribute results to media tactics, quantify long-term effects, and forecast sales and ROI results.
Where we are with marketing ROI measurement Michael Wolfe
This article discusses current state of affairs for marketing ROI measurement. There is dissatisfaction with the status quo and this article outlines a completely new approach.
The Complex Journey to Unified Marketing AnalyticsJoy Joseph
The discerning marketer today is well aware that the annual “set it and forget it” marketing measurement process is a relic of the past. Marketing strategy has evolved to a dynamic “always-on” state, and performance metrics are needed on demand. Marketers have already been using marketing mix models in a major way to support this iterative process of measurement, optimization and simulation. They are, however, beginning to reevaluate systems currently in place given the increased complexity of targeted and programmatic advertising in a highly fragmented digital advertising landscape. Traditional manual processes are unable to scale to support this dynamic and complex planning environment. To add further confusion to the chaos, another potential rival methodology, attribution modeling, evolved to fill the gap of individual digital conversion measurement.
This Advertising Research Foundation webinar, hosted by IRI’s Joy Joseph and Blue 449’s George Musi, lays out a perspective on why marketers need to leverage a more integrated approach between different measurement systems, as well as what decisions can be supported by which systems.
Iri growth summit_media and promotion effectiveness_v3Joy Joseph
IRI and Turner partnered in mining marketing-mix studies
across 62 brands representing $20 billion in sales and
$3 billion in marketing spend across food, beverages,
health care, beauty and home care aisles. The objective
was to help marketers determine the most efficient
marketing allocations and guide organizations to make
marketing investments that provide short- and long-term
growth.
Case study shows how a restaurant chain rediscovered its purpose. By engaging in "voice-of-the customer" analytics, this restaurant was able to identify why their volume was declining and what they needed to do to rectify some shortcomings in their product offering. VOC Analytics uses a proprietary approach for converting textual brand reviews on social media into predictive metrics.
Future of Tracking: Transforming how we do it not what we doKantar
The slides from ‘Digital Transformation of Tracking’ webinar presented on BrightTalk on 28th February 2017. In this webinar Mark Chamberlain and Alex Taylor discuss how changes in consumer behaviour, increased business pressures and new technologies have created both opportunity and disruption across all industries. Like every other industry, research is in the midst of its own transformation affecting not what we do but how we do things.
A paradigm shift in advertising effectiveness measurementMichael Wolfe
This report shows a new way to measure advertising copy or creative. In contrast to current regimes which have changed little over the past 50 years and have not adapted to a market with more ads and channels, the ABX system here described is both faster, less costly, provides wider coverage of channels and has been validated vis a vis brand sales performance.
The Print Campaign Analysis by Millward Brown DigitalSanoma Belgium
The Print Campaign Analysis, a “meta-analysis “ conducted by Millward Brown, an authority in the assessment
of advertising impact, examined nearly 100 ad effectiveness studies that the advertisers themselves had
originally commissioned. Millward Brown’s report finds that print advertising results in the greatest increases
in persuasion metrics—brand favorability and purchase intent—compared to other platforms. These
advertiser-generated data also reveal that when advertisers used print magazine in combination with other
platforms, they were most successful in raising outcome metrics, leading to the conclusion that digital
platforms work best when they are connected to powerful traditional media, such as print.
12 Best Practice & Real-World Lessons From Marketing Sciencey lessonsMichael Wolfe
This paper shows 12 key startegic lessons derived from analytics or marketing scence which under score the value that this discipline brings to higher levels of busness performance.
One of the crucial trends nowadays will be the growth of attribution modeling. However, many savvy marketers are still missing the opportunity to reap the benefits of attribution modeling, hence this whitepaper is aimed at providing a comprehensive overview of what marketing attribution is all about.
Innovations in marketing effectiveness measurement Michael Wolfe
A new and innovative approach in marketing ROI measurement. Goes beyond traditional marketing mix models by 1) developing long-term ad effects measurements, 2) measuring media message and creative, 3) quantifying the interactions or synergies across the marketing mix and 4) measuring the voice-of-the customer through social media
The Smart Cube | Marketing Mix Modeling: An Old Remedy for New IllsMelissa Luongo
Authors:
Ankit Abraham Sinha, Senior Analyst
Sidharth Sreekumar, Assistant Manager
What is Marketing Mix Modeling (MMM)?
MMM is the use of statistical analysis to estimate and predict the impact and effectiveness of media channels, price changes, promotions, and external factors on the sales volumes of a company. This helps demystify the relationship between a company’s marketing spend and its bottom line.
Measuring the Effectiveness of Marketing Spend Using MMM
Increasing Marketing Spend
As global ad spending increases, it is imperative for companies to ensure that they get the best bang for their buck. In this scenario, the need to measure the impact of various marketing media on sales and deploy marketing funds efficiently is even greater.
The Need to Measure the Impact of Marketing
According to an April 2014 study by VisionEdge Marketing and ITSMA, 85% of marketers polled were of the opinion that the pressure to measure the value and contribution of marketing is increasing. In addition, a May 2014 study by Ifbyphone states that 60% of marketing executives report marketing metrics to their business leadership teams at least on a monthly basis. This highlights the increasing emphasis being laid by business leaders on the need for regular and more accurate measurement of marketing metrics that highlight the impact of marketing spend on business performance.
Top 20 Reasons Why Agent-based Modeling is Disrupting Marketing MixThinkVine
Misallocated ad dollars may be costing brands more than 25 percent in lost sales. Based on an analysis of ThinkVine customers with average annual sales of more than $1 billion, we found that companies were spending too much or too little on specific media 85 percent of the time. By optimizing their marketing budgets, the companies added anywhere from 7 to 81 percent in additional revenue attributed to marketing activities – an average of 28 percent.
Don’t lose out on the additional sales your marketing could be driving. Brands have been relying too heavily on outdated, backward-looking marketing mix methods that leave money on the table.
Companies are now turning to agent-based modeling to make better strategic decisions that will deliver the results they need, and here is why.
Learn How a New Kind of Marketing Mix Modeling is Better for Media PlanningThinkVine
This presentation discusses the use of agent-based modeling and its proven advantages to media planners, including the abilities to create effective media plans based on consumer differences, accurately attribute results to media tactics, quantify long-term effects, and forecast sales and ROI results.
Where we are with marketing ROI measurement Michael Wolfe
This article discusses current state of affairs for marketing ROI measurement. There is dissatisfaction with the status quo and this article outlines a completely new approach.
The Complex Journey to Unified Marketing AnalyticsJoy Joseph
The discerning marketer today is well aware that the annual “set it and forget it” marketing measurement process is a relic of the past. Marketing strategy has evolved to a dynamic “always-on” state, and performance metrics are needed on demand. Marketers have already been using marketing mix models in a major way to support this iterative process of measurement, optimization and simulation. They are, however, beginning to reevaluate systems currently in place given the increased complexity of targeted and programmatic advertising in a highly fragmented digital advertising landscape. Traditional manual processes are unable to scale to support this dynamic and complex planning environment. To add further confusion to the chaos, another potential rival methodology, attribution modeling, evolved to fill the gap of individual digital conversion measurement.
This Advertising Research Foundation webinar, hosted by IRI’s Joy Joseph and Blue 449’s George Musi, lays out a perspective on why marketers need to leverage a more integrated approach between different measurement systems, as well as what decisions can be supported by which systems.
Iri growth summit_media and promotion effectiveness_v3Joy Joseph
IRI and Turner partnered in mining marketing-mix studies
across 62 brands representing $20 billion in sales and
$3 billion in marketing spend across food, beverages,
health care, beauty and home care aisles. The objective
was to help marketers determine the most efficient
marketing allocations and guide organizations to make
marketing investments that provide short- and long-term
growth.
Case study shows how a restaurant chain rediscovered its purpose. By engaging in "voice-of-the customer" analytics, this restaurant was able to identify why their volume was declining and what they needed to do to rectify some shortcomings in their product offering. VOC Analytics uses a proprietary approach for converting textual brand reviews on social media into predictive metrics.
Future of Tracking: Transforming how we do it not what we doKantar
The slides from ‘Digital Transformation of Tracking’ webinar presented on BrightTalk on 28th February 2017. In this webinar Mark Chamberlain and Alex Taylor discuss how changes in consumer behaviour, increased business pressures and new technologies have created both opportunity and disruption across all industries. Like every other industry, research is in the midst of its own transformation affecting not what we do but how we do things.
A paradigm shift in advertising effectiveness measurementMichael Wolfe
This report shows a new way to measure advertising copy or creative. In contrast to current regimes which have changed little over the past 50 years and have not adapted to a market with more ads and channels, the ABX system here described is both faster, less costly, provides wider coverage of channels and has been validated vis a vis brand sales performance.
The Print Campaign Analysis by Millward Brown DigitalSanoma Belgium
The Print Campaign Analysis, a “meta-analysis “ conducted by Millward Brown, an authority in the assessment
of advertising impact, examined nearly 100 ad effectiveness studies that the advertisers themselves had
originally commissioned. Millward Brown’s report finds that print advertising results in the greatest increases
in persuasion metrics—brand favorability and purchase intent—compared to other platforms. These
advertiser-generated data also reveal that when advertisers used print magazine in combination with other
platforms, they were most successful in raising outcome metrics, leading to the conclusion that digital
platforms work best when they are connected to powerful traditional media, such as print.
12 Best Practice & Real-World Lessons From Marketing Sciencey lessonsMichael Wolfe
This paper shows 12 key startegic lessons derived from analytics or marketing scence which under score the value that this discipline brings to higher levels of busness performance.
One of the crucial trends nowadays will be the growth of attribution modeling. However, many savvy marketers are still missing the opportunity to reap the benefits of attribution modeling, hence this whitepaper is aimed at providing a comprehensive overview of what marketing attribution is all about.
This is the presentation from our Exclusive Sydney CBD Event 7:30am August 24th 2017 as Industry Leaders shared their insights and thoughts on how to achieve scale and success with Social.
Todays top performing companies compete based on customer experience. Todays customers want a SMARTER customer service experience through their social channel of choice — one that is both FAST and PERSONAL. In fact, 64% of customers expect companies to respond and interact with them in real-time or they will take their business elsewhere.
What was covered?
* Social Customer Service & Crisis Management - How to offer a ubiquitous and robust service experience across social
* Social Listening - How to drive strategic decisions across your business based on customer and competitive insights
* Social Leads - How to generate Social leads for your sales team to nurture
* Command Centre - How to drive change and awareness within an organisation by making your internal stakeholders aware of everything that's happening on Social, Email, Web, Ads, Journeys and through Sales Leaderboards
At this exclusive event we learned how major brands are able to listen to their customers at scale, control communications in a crisis, and engage with their customers with personal service, in an instant... creating advocacy in this culture of immediacy.
Agenda:
* 7:30am Registration and Networking
* 8:00am Opening Remarks
* 8:05am Presentation: Adam Brown
* 8:45am Panel Discussion
* 9:05am Closing Remarks
* 9:15am Networking
Presenter
Adam Brown is Executive Strategist for Salesforce Marketing Cloud. He and his team deliver integrated social marketing strategy to customers and work with product teams to develop the best marketing products and solutions in the industry. Before joining Salesforce in May of 2013, Adam was Executive Director of Social Media at Dell, where he led the company’s consumer strategy around social media marketing, engagement and social commerce initiatives. Adam joined Dell in 2010 after spending four years creating and leading the Office of Digital & Social Media at The Coca-Cola Company.
What is multi-touch point attribution, and which model perfectly defines your customer's buying journey? Read our expert blog to learn more.
https://www.virtueanalytics.com/multi-touch-point-attribution/
Harnessing the Power of Predictive Models for Marketing Campaign Optimization...Daniel McKean
In the fast-paced world of digital marketing, making data-driven decisions is not just an advantage; it's a necessity. Among the plethora of tools and techniques at the disposal of marketers and data analysts, predictive models stand out for their ability to transform complex marketing challenges into opportunities for strategic optimization.
Driving marketing performance in financial services is subject to unique considerations. Diverse set of distribution channels, complex customer segments, a need to balance branding and promotion, and multiple outcome measures impacting customer value are factors to consider.
From Digital Attribution to Marketing Mix ModellingPetri Mertanen
MeasureCamp Amsterdam 2018. We are good when it comes to measuring advertising but should you also thing what kind of effect other marketing P's have on sales?
GfM Research Series: Successful Marketing in a Digital WorldChristoph Spengler
How can we control and target our marketing
during the digital transformation based on a firm
foundation for planning and decision-making?
Traditional methods and measurement tools run up
against their limits when trying to create a comprehensive
picture of customer behavior in a multichannel
world. At most they only show a small slice
of reality – and they are unable to capture very much
of new developments. Questions like: “What touchpoints
do customers really use?” and “How important
are these?”, remain unanswered.
Measurable and comparable touchpoint
management helps managers maintain an
overview and take decisions faster.
Successful Marketing in a Digital World - GfM Research SeriesChristoph Spengler
GfM Research Series: Successful Marketing in a Digital World
If they want to offer customers a consistent, brandtypical experience and excellent service in future, successful companies will have to restructure every area of market development: marketing, sales and communication.
Developing effective value creation in digital advertising. Focuses on how programmatic media buying strategy can identify value which enables brands to build upon customer relationships. By aligning operations and analysis around overall marketing strategies programmatic media industry participants can increase the vale they provide.
Predictive Analytics: How This Revolutionary Technology for Strategic Marketi...Media Needle
An advanced software solution using agent based modeling to recreate a virtual marketplace with your target markets networked behavior patterns. All touch points in the entire consumer journey are connected and include key dynamics such as brand sentiment, word-of-mouth, social media, online and offline channels. Vet your ROI on every strategic move your brand makes before doing anything and use this as unfair advantage against your competition.
Media Needle's strategy simulation platform enables brands to accurately forecast performance of advertising campaigns and key business decisions. Delivering a better understanding of the risks and outcomes these simulations enable brands to develop a more accountable and refined marketing strategy.
Demystifying Marketing Attribution A Comprehensive Guide to Data-Driven Mark...Growth Natives
Unlock the secrets of effective marketing attribution with our comprehensive guide, "Demystifying Marketing Attribution." In this enlightening PDF, we delve into the intricacies of data-driven marketing decisions, offering a thorough exploration of the tools and strategies that empower businesses to make informed choices.
Discover the key principles behind marketing attribution and learn how to navigate the complex landscape of customer touchpoints. From first interaction to conversion, our guide breaks down each step, providing insights into the role of data in shaping successful marketing campaigns.
Whether you're a seasoned marketer or just stepping into the world of data-driven decision-making, this guide is designed to demystify the often-confusing realm of marketing attribution. Gain a deeper understanding of multi-channel attribution models, attribution windows, and the significance of various data sources in shaping your marketing strategy.
Armed with practical tips and real-world examples, this guide empowers you to optimize your marketing efforts. Uncover the mysteries of attribution modeling, attribution weighting, and attribution platforms to make confident decisions that drive results
Similar to Shows approach which expands the breadth of what marketing-mix models c (20)
12 keys to innovative marketing planning (002)Michael Wolfe
This document discovers 12 ways or tools that marketing professionals can use to drive more returns and improve the effectiveness of their marketing plans.
Measuring the Lonng-Term Effects of AdvertisingMichael Wolfe
To those who do Marketibng-Mix modeling, one understands that these tools tend to have a singlular and exclusively short-term focus on marketing measurment. This white paper makes a case to including long-term measures in these models, expecially loking at the long-teerm efffects of advertising. This article makes a good business case for doing this and provides sine reak case studies to support his case.
Medical Office Marketing ROI MeasurmentMichael Wolfe
This is a case study pertinent to hospitals and multi-office medical and dental practices that will enable them to do smarter and more effective marketing through a marketing effectiveness measurement system
This deck introduces the ABX ad testing system, a paradigm shift in how companies can evaluate their paid and pre-test media. Their model conforms to the rules of faster, cheaper, deeper and better.
This presentation outlines an approach for measuring gender bias in advertising. Called the Gender Equality Index, this was developed by the company Advertising Benchmark for the ANA or Association of National Advertising
Likeability and advertising effectivenessMichael Wolfe
Explores case of Colonel Sanders in KFC advertising. Copy test data reveals a high level of "dislike" of the character, but this has no impact on overall ad effectiveness and even less of an impact on customer "purchase intent". This all raises the question of whether ad likeability is even a factor for assessing ad effectiveness and whether an ad sells product.
Radial Landscape Mapping: A new tool for brand positioningMichael Wolfe
Radial Landscape Mapping is a visualization tool that displays key data representing and differentiating competitive brands and shows the core brand perceptions of brands relative to their competitive set.
Marketing ROI case for banking & financeMichael Wolfe
Following is a case study showing marketing effectiveness analytics for a banking and financial services firm in the South Central US. A part of the challenge here involved estimating the impact that Hurricane Katrina had on this banks and the measurement of marketing ROI and impact in some new markets. in the end,. as is true for the banking sector, actual ROI of marketing is quite high and there are substantial opportunities for accelerate revenue growth with more effective marketing spend.
Auto brand marketing optimization modelsMichael Wolfe
This is a case study of a multi-line auto manufacturer and its quest to develop marketing optimization models which will help their brand gain higher marketing returns and accelerate their business growth. These efforts were successful and drove the company to a higher sales increase in the succeeding year.
Marketing Response and Optimization Model for CasinosMichael Wolfe
this is a case study for a 5 casino property gaming firm. This is a marketing response modeling project where insights gained enabled this firm to accelerate growth in the following year and improve their marketing ROI via a more optimized marketing spending plan.
Econometric Forecast Model for Housing Components ManufacturerMichael Wolfe
Forecasting demand in a cyclical business such as housing components is difficult & tricky. In this case, we developed an econometric model for housing components driven by order backlogs, housing starts, remodeling spending and pricing.
Finding the waste in marketing spendingMichael Wolfe
Every marketing program has about 25-70% of its spending occurring on initiatives which generate very low returns which only generate a fraction of the break-even revenue of its spending. This analytics for identifying these more wasteful activities and the upside resulting from trading the high productive marketing activities for the more wasteful ones.
Marketing ROI Modeling and Analytics for Retail Energy CompaniesMichael Wolfe
Unregulated utilities need to spend considerable sums on media and marketing in order to compete for subscribers. This study shows how one company could measure marketing ROI, reduce wasteful marketing spending and optimize its spending to drive significantly higher revenue growth.
Marketing effectiveness analytics & ROI measurement for Auto Services RetailingMichael Wolfe
Case where new & used car dealership chain needed to improve the effectiveness of their media spend and save money by eliminating ineffective programs. Using econometric models, this analysis showed how this chain was able to save 28% on their marketing spend and direct their investments toward more productive activities and grow overall sales 2.4%
The Missing Element in Marketing MeasurementMichael Wolfe
While marketing-mix modeling has long been a gold-standard of marketing ROI measurement, it is lacking one very important driver of the business: the voice-of-the-customer. This presentation illustrates how leveraging a metric from social media-brand-experiential comments represents a large and very important driver of brand performance.
Developing a best-in-class innovation enterpriseMichael Wolfe
Innovation is the life-blood of successful business and commercial growth. This paper outlines what companies need to do in order to rise to being “best-in-class” innovation-driven enterprises. Here, we outline the steps to measure performance and set up plans and measurements for rising to the top as an innovation-driven business enterprise and what are the key factors necessary for becoming “best-in-class”
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
2. Content
• Marketing-Mix Modeling at the Crossroad & its Shortfalls 4-5
• Next-Generation Marketing-Mix Models 5
– It starts with the basics of blocking and tackling 6
– No Silos for marketing and Marketing Synergies 7-9
– Measuring the Long-Term Effects of Advertising 10-12
– Addressing Multi-Touch Marketing Attribution & Digital ROI 17-22
– Building in the Voice-of-the-Customer into MM Models 23-36
– Simulation and Real-Time Marketing-Mix Models 37-38
• Analytics Portfolio 39
• Global-Analytics Partners 40-42
• Contact Us 43
2
3. Marketing-Mix Modeling at a Crossroad: Marketing-
Mix Models Falling Short
• Marketing-mix models have been referred to as the de facto standard for marketing measurement.
• Yet, with all the dramatic change in the marketing landscape, there has been little to no change in how
these models calibrate and measure marketing ROI over the past 30 years. The tools have failed to adapt
and this has stimulated a chorus of criticisms, wondering if Marketing-Mix Modeling is obsolete
• In a recent AdAge article entitled “Marketing-Mix Models Get Pushback As Media Landscape Changes”
(Apr. 2013), we hear a growing chorus of critics.
• “Some critics believe the models have been wrong all along, and work even worse after three decades of
change in the media landscape. They say the models underestimate the impact of advertising, particularly
of broad-reach network TV; overstate the value of price promotion, mislead marketers into buying thinly
rated programming; wrongly downplay risks of going dark for weeks on end; and fail to account for how
online search has made all advertising more effective”.
• Marketing-Mix Modeling has been criticized for its focus only on short-term marketing response and, for
the most part, not adapting to more advanced methods for measuring long-term marketing impacts and
customer loyalty and repeat-purchase dynamics. Because MM models mostly focus only on short-term
effects of adverting, this has relegated the ad investment to negative ROI in about 85% of cases. Without
consideration of the larger long-term effects of advertising, there is a major under-estimation of the true
value of advertising and marketing and this has caused an incorrect focus on short-term only marketing.
• There seems to be a consensus that a new paradigm needs to be developed for marketing measurement.
However, most MMM vendors have not put forth answers to some of these known short-comings.
3
4. Marketing-Mix Modeling at a Crossroad
A lot of the underlying method of MM models relies on statistical assumptions which assume
complete independence of the marketing drivers. Marketing can not be relegated to silos. All of
this ignores the synergistic and more complex symphony represented by multiple marketing
activities acting together.
Marketing is all about a brand’s “relationship” with customers. Yet, through all of this, “the voice-of-
the-customer” remains silent in the MM modeling exercise. The proper step for MM modeling
requires developing a means for measuring the various aspects of the customer-brand-experience
and clearly understanding the brand value proposition directly from the customer’s perspective
MM modeling focuses pretty much exclusively on marketing channels. Media effectiveness is seen
through the lenses of TV, radio, print or digital channels. All of this ignores that marketing is really
about “message and communication”. MM Modeling needs to change its focus and measurement
towards the effectiveness of ad message and creative. This is a major missing piece that limits MM
Modeling from being an effective and powerful tool for forming marketing communications
strategies.
MM modeling has also been criticized for its inability to accurately address the issue of digital multi-
touch attribution. Single equation econometric models often yield biased solutions, with extreme
solutions favoring the media or activity closest in proximity to the sales conversion and giving no or
little credit to key touch-points along the customer journey path. This means that more advanced
“multi-equation” econometric solutions need to be employed which will better account for and
accommodate the actual pathways and media touch points of the customer journey.
We think that it is time for something different: a paradigm shift.
4
5. Incremental Contribution from marketing
Return on Investment per £1 spent Optimize spend, maximise sales
Develop relationship between sales and drivers
Next-Gen Marketing Mix starts with blocking & tackling
5
6. …pushing the boundaries.
Next Generation Marketing-Mix Models
TV
RADIO
NEWSPAPER
PAIDSEARCH
6
Effectiveness Modeling (econometrics) has not changed a great deal over the last 30 years.
We fundamentally believe that marketing and media channels do not operate in silos; but most
statistical models treat them as such. We employ advanced non-linear methods which account
for direct and indirect effects from marketing drivers.
10. Measure long term ad effects
Most advertising creates an initial short term lift in sales and a prolonged long term
impact. This is generated through repeat purchase and customer loyalty.
Long Term Effect
10
11. Many MM Vendors do not know how to measure Long-Term ad
effects and counsel clients to simply multiply short-term media
by 2. This is wrong! For this brand, where 90% of sales were
repeat buys, Long-Term ad effects were 15x
66.05%
7.29%
1.82%
0.50%
0.21%
0.02%
1.45%
22.67%
33.95%
Incremental Contributions to Total Neutrogena Sales
Baseline Dist.@Min Mdsg.Ftr Mdsg.Displ
Mdsg.F + D ST Adv.Spend ST Adv.Creative Long-Term Adv 11
12. The financials of advertising dramatically
change from -$100K to 2 .7 million dollars!
($500)
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
Short-Term Effect Only With Long-Term Effects
($100)
$2,720
HBA Brand Annual Ad Net Returns
* Assumes 20% EBITDA/Sales Margin
12
13. Media copy quality measurement
0
50
100
150
200
250
300
Radio Ad 1 TV Ad 2 Digital Ad 3 TV Ad 4
GRPs/Spend
Creative
13
Media content and copy quality can be separated and measured. This has
implications for design, content and message mix. 60 to 80 percent of short-
term advertising is message or creative and not spend/GRPs
Note: we can apply this technique to digital media also.
14. In the ideal world, spend on an ad-by-ad basis would align
perfectly with ad sales lift, but this is not the case. The
true situation is most often highly inefficient and
wasteful!
Correl.=0.298
0
20
40
60
80
100
120
140
160
3 5 7 9 11 13 15
SPENDPERADSQRT
Ad SALES LIFT SQRT
12
15. However, when we use copy test scores from ABX, it has
proven to align and correlate extremely well with individual
ad sales lifts. This provides a great resource for allocating
marketing funds across individual ads!
Correl.= 0.743
4
5
6
7
8
9
10
11
12
13
3 5 7 9 11 13 15
ABXINDEXCREATIVESCORESQRT
AD SALES LIFT SQRT
Using the ABX metric to allocate media budget by ad would
have generated + $21MM (2%) in incremental revenue for
Neutrogena
13
16. Effective Measurement of Digital Media
Annual Marketing Contributions
86.2%
0.0%
2.9%
0.7%
0.9%
1.9%
1.2%
1.2%
3.0%
0.2%
1.8%
13.8%
Baseline
Display Premium
Display Network
Paid Search
SEO
Branded TCP TV GRPs
Sponsorship (ITV Weather )
Cinema Ad
Radio
Press
GDP Effect
1.4 million in marketing spend generated almost 13.4 million pounds in revenue
sales. Total media accounts for about 12% of total sales. Radio, Digital Display and
TV were the largest drivers of car sales.
16
17. Addressing the issue or “multi-touch”
marketing attribution bias
• A common and well-known criticism of current MM models is their failure to
accurately cover and reflect the influence of different channels, especially digital
ones, that reflect the customer journey towards sales conversions. Frequently,
what we find is a bias that favors the specific channel closest to the sales
conversion, attributing most of the impact to that single last-touch point.
• MTA or multi-touch attribution covers the challenge of attributing accurate impact
of our marketing and advertising efforts across multiple devices (desktop, laptop,
mobile, TV) and/or channels.
• On the next slide, we illustrate how different model methodologies generate
results from the same data case study.
• Our findings reveal that common “single equation” econometrics yields extreme
results, assigning near full credit to one single channel.
• By using more advanced and multi-equation econometric methods, we are able to
develop models which simulate a path-solution rather then point-in time
responses. These more advanced multi-equation models allow for each
marketing channel to assume its more accurate impact based on the true
consumer purchase path. 17
18. Percent Contributions Single Eqtn. OLS 2SLS SUR Nested NNet
Digital Website Page Views [lag 3] 4.27 0.83 0.89 0.56
Display Ads 3.44 3.19 0.88
Digital.Pd.Search 0.51
Mass.TV 0.44 0.44 0.44 0.43
Mass.Print 0.09 0.16 0.17
Trend (4.05) (4.05) (4.06) (0.85)
Final LongLTVariable .KalmanFilter 28.40 28.40 28.34 4.49
Base 70.94 70.85 71.04 76.91
Total 100.00 100.00 100.00 100.00
Synergy 16.90
6.0 5.9 6.1 1.8
Conventional single –equation models are
biased with respect to multi-touch attribution
18
(5.00)
(4.00)
(3.00)
(2.00)
(1.00)
-
1.00
2.00
3.00
4.00
5.00
6.00
Single Eqtn. OLS 2SLS SUR Nested NNet
Model Percent Contributions
Trend
Mass.Print
Mass.TV
Digital.Pd.Search
Display Ads
Digital Website Page Views [lag 3]
Multi-Equation approaches are more balanced and overcome MT Attribution Bias
Single equation solutions often biased in
favor of activity closest to sales conversion
19. Single Equation Regression Model
Sales
Web
Page
View
TV
Print
BaseTrend
Lag 3
1) Sales is attributed to Web Page
Views, TV, Base and Trend
2) Numerous variables
are not significant +
multicollinear
19
Long
Term
Media
3) Very high attribution
on 1 variable (last
touch?)
Competitor
Ads
Display
Ads
Paid
Search
19
The most common approach to MM modeling is single-equation models, which have a high
likelihood of generating biased attribution due to “last-touch attribution bias”.
20. Two Stage Least-Squares Model
Sales
Web
Page
View
TV
Print
BaseTrend
Lag 3 Lag 1
1) Uses two equations, also referred to
as instrumental variable approach
2) Sales and Web Page Views have a
reciprocal relationship which is
lagged
3) Display ads are indirectly
contributing to sales via Web Page
Views
4) It appears that competitor ads are
also driving some traffic to own
Home Page.
5) Direct & Indirect Effects
Paid Search not
influencing sales or
web page views.
20
Paid
Search
Display
Ads
Competitor
Ads
Long
Term
Media
20Multi-equation models are better suited for discovering the nature and direction of complex
indirect or reciprocal relationships and interactions within the data models
21. Seemingly Unrelated Regressions
(SUR)
21
Display
Ads
Sales
Web
Page
View
TV
Long
Term
Media
Print
Trend
This variables is not
significantPaid
Search
Lag 1Lag 3
1) Like SEM for time series
modeling. SUR is a true Multi-
equation system
2) When errors are correlated,
solution is a path rather than
discrete data variables. This path
can be assumed to be the
attribution path.
3) But when the regression errors really
are unrelated, then we are just
generating single eqtn. OLS results
Competitor
Ads
21
22. Nested Neural-Network Model
22
Sales
TV Print
Display
Ads
Paid
Search
Long
Term
Media
All
MarCom
Competitor
Ads
Web
Page
Views
Trend
1) All MarCom Variables pooled
into meta-variable and
dynamically weighted
2) Good for discovery of non-
linearity, interaction and synergistic
effects without a priori knowledge
3) Have undeserved reputation for
being black-box & can be trained to
be stupid.
24. Can social media be measured?
1 The Growing Importance of Word of Mouth, www.boundless.com
24
Social Media really isn’t Media as we know it. It doesn’t have “inventory”
and it’s not meant to deliver “ads” like traditional “media”
Marketing was once seen as a one way relationship, with firms
broadcasting their offerings and value proposition.
• Now Marketing is seen more as a conversation between marketers and customers.1
• Social media is a key and critical channel for this two-way communication
Current social media metrics are expressed in terms of “sentiment”
• Positive and negative commentaries about brands
• These metrics do not seem to explain or predict purchase behavior
Many have given up and say social media can not be measured
25. If we remember that social media is a form of word-of-mouth, then words
matter!
• The semantics, linguistics and context of the conversation matters
Our Social Media analysis is based on Stance-Shift Analysis
• Uses the Social Media conversations about your Brand as input
• Apply linguistic principles of sentiment and tonality
• Results in an engagement score that is a translation of a customer’s “personal” and “emotional”
relationship with brands, as revealed through language & semantics….Social Engagement Index (SEI)
• Academically published, peer reviewed & validated.2
Stance-Shift Analysis translates the consumer’s qualitative emotions into
quantitative metrics.
Our approach to measuring Social Media
2 Stance Analysis: social cues and attitudes in online interaction, Mason, P , Davis B, In E-Marketing Vol. II . 2005.
25
26. Developing the Social Engagement Index (SEI)
Net Positive SEI Index
1. Mine all brand related social media
reviews and commentary.
2. Parse into positive & negative
review groups
3. Apply Social Engagement Index
algorithm to “score” reviews
4. Time code by period and aggregate metrics
Positive
Reviews
Negative
Reviews
Positive
Scores
Negative
Scores
LOW MEDIUM HIGH
HIGH 0 5 7
MEDIUM -5 0 5
LOW -7 -5 0
Emotional Effect
Personalisation
26
27. SOCIAL
ENGAGEMENT
INDEX (SEI)
Conversations are scored on personal
and emotional content
“I HAD A DIET COKE FOR LUNCH TODAY”
“THE WARM DIET COKE WAS RATHER BLAND”
27
“I REALLY LOVE MY COKE WITH PIZZA”
“I LIKE THE TASTE OF SPRITE WITH LEMON”
“MY COKE HAS LOST ITS FIZZ AND TASTES AWFUL”
28. SEI shows superior correlationsto brand sales compared
with other SocialSentiment Metrics
82.9%
14.8%
9.9%
7.7%
5.9%
2.8%
-3.2%
-20% 0% 20% 40% 60% 80% 100%
SOCIAL ENGAGEMENT INDEX POS/NEG RATIO
METRIC 5 POS/NEG RATIO
METRIC 1 POS/NEG RATIO
METRIC 4 POS/NEG RATIO
METRIC 6 POS/NEG RATIO
METRIC 2 POS/NEG RATIO
METRIC 3 POS/NEG RATIO
Comparison of correlation to sales for the SEI versus the six leading sentiment metrics
28
29. The correlation* to sales over time shows the SEI has Predictive Power
29
ACID TEST: SEIsm has proven linkage with brand sales
Correlation = 86.4%
Correlation = 84%
Correlation = 81.1%
Correlation = 83%
Correlation = 83%
* Lead lag analysis has confirmed that causation is only one way – the SEI to a large degree is able to drive hard commercial metrics.
30. Applications of the SEISM
Packaged inside a media mix model, the SEI
acts as the key indicator for social media
‘word of mouth’.
We are able to determine the return on
investment for social media and provide
steer around the most effective channels and
spend.
SEI to help uncover
market insights
The SEI is also the primary tool used to
understand the degree of brand engagement
as it transpires through the use of language.
• Understand drivers to positive engagement.
• Measure the efficacy of individual campaigns.
• Develop content strategy that has cut through.
• Enhance the execution of sporting events.
• Assess brand perception in a competitive sense.
• Understand consumer discourse and manage crises.
SEI to measure social
media ROI
30
31. 31
SEI to measure social media ROI
We find that conventional advertising has both a “direct” and “indirect” impact on sales due to
its influence on social media conversations and the SEI.
The large contribution from the SEI support the notion that this is a “word-of-mouth” effect
67%
8%
3%
2% 2%
10%
5%
11%
20%
Marketing Contributions
Base Sales Direct Alpha Brand Mass Media Direct Alpha Brand Digital Media
Direct Social Media Social Media on SEI Mass Media on SEI
Digital Media on SEI SEI Base
Net driven by media
SEI
Engagement
Sub-model
32. 32
The impact of Social Media sentiment
A key insight we uncovered across clients is the difference between “positive” and “negative”
brand conversations
Negative-toned conversation have a significantly greater net impact on brand sales
+4.4%
+16.5%
0%
5%
10%
15%
20%
Positive Sentiment Negative Sentiment
The absolute impact from positive &
negative consumer reviews
Marketers need to develop strategies and tactics to immediately mitigate “Negative News”
and prevent them from going Viral.
33. Much like other marketing and media metrics, we can deconstruct the different elements of
the SEI metric into the channels driving social engagement and brand sales.
Source: Nielsen BuzzMetrics data as of November 27, 2011
Social channels driving consumer
engagement and sales
33
34. Most Important Drivers to
Positive SEI.
Using this insight, the
client developed a ‘bring
a friend, and get one
coffee free’ to drive store
level sales.
Positive SEI
3.93 = 100
Place2HangOut
>5.46= 211
9.1%
Place2HangOut
<5.46 = 83
91.9%
ToMeetPeople>
9.43 = 325
2.6%
ToMeetPeople<
9.63 = 188
6.5%
Atmosphere
>14.0 = 466
0.6%
Atmosphere
<14.0 = 288
1.9%
To Meet People
>5.4 = 229
3.8%
To Meet People
<5.4 = 85
85.5%
Beverage A
>6.4 = 271
7.7%
Beverage A
<6.4 = 74
77.8%
Place2HangOut
>3.6 = 126
5.9%
Place2HangOut
<3.6 = 76
71.9%
Beverage B
>5.2 = 211.1
1.6%
Beverage B
<5.2 = 67
70.3%
Note: Separate analysis - Classification & Regression Trees (CART)
The tree starts with an average SEI score of 100; and each level indicates a higher or lower SEI based on
an SEI score for a topic. The percent represents the percent of the sample in each segment.
Develop In-Market strategies based on
“Why” consumers use your brand
34
35. Alpha_P1
Beta_P1
Note: Separate analysis - Adapted Statistical Correspondence Analysis
Example: Global Coffee Chain
Bubble size represents the buzz/volume of chatter (SEI Conversational Clusters)
Alpha_P2
Beta_P2
Gamma_P1
Gamma_P2
Net Chatter around value
and price
Net Chatter around coolness, funky,
style, Décor
Net Chatter around taste and
product quality
Net Chatter around in-store
customer experience
Delta_P2
Delta_P1
Good value
Coffee Price
Food prices
Staying in
Seating/chairs
Toilets
Richness
Latte
Amazing taste
Like no other
Cool brand
Funky
Stylish Artwork/Decor
Visualize social media brand conversations
35
36. Introducing…
Bottom-Line Analytics & GAP is a full service consulting group focusing on
marketing effectiveness and brand performance analytics.
Our modeling experts have a total of over 150 years of direct experience
with marketing mix modeling with direct experience in over 40 countries
We are dedicated to the principles of innovation, excellence and
uncompromising customer service.
Everything we do is geared towards improving commercial performance.
36
&
37. Play out marketing What-if scenarios
An interactive dashboard allows you to simulate different marketing mix/spend
scenarios and assess the resultant impact on sales and profitability.
1. Set marketing
budgets.
2. Set your
spend levels
across media
channels
3. Assess the
resultant
impact on sales
& profit
37
38. Continuous model updates
allow for real-time simulation
and planning
An interactive dashboard allows you to
simulate different marketing mix/spend
scenarios and assess the resultant impact
on sales and profitability.
39. Why
Impartial and
Independent
Full Service
Analytics
Capability
VOC
Measurement
With Social
Media
Marketing Mix Modelling 3.0
Ad Copy ROI Measurement
Multi-Touch Attribution Models
Marketing Synergies
Long-Term Ad Effect
Pricing Optimisation
Radial Landscape Mapping
Key Drivers Analysis
Demand Forecasting
Customer Satisfaction Modelling
Performance Analytics Dashboards
Segmentation Analysis
Marketing Decision Support Tools
Our proprietary approach
to social media
measurement is unrivalled.
Objective approach to
media measurement.
39
&
40. Full Service
Analytics
Capability
Social Media ROI
Marketing Mix Modelling
Pricing Optimization
Radial Landscape Mapping
Key Drivers Analysis
Demand Forecasting
Customer Satisfaction Modelling
Digital Performance Analytics Dashboards
Segmentation Analysis
Decision-Support Systems
40
BLA is a trusted advisor to a wide array of clients
We believe in the continuous innovative application
of analytics to advance customer centric decision
making for improved business performance.
41. It’s all About Results
Company Results
Coca-Cola
Brought marketing ROI modeling to company for first time in 1996. In first year developed models for
Coca-Cola, Coke Light, Fanta and Sprite in 12 Countries. Year two sales gains over prior year exceeded
$300 million.
Starbucks
Developed measure of customer-brand experience using social media. Discovered that Starbucks main
strength lies in its in-store experience. Successfully developed brand positioning for Frappucino and
Via Coffee. Sales growth improved from +7 to +11 percent
McDonald's
Identified significant upside growth opportunity to drive higher restaurant sales by investing
significantly more in "dollar-value meals" one year after launch in 2005. Per recommendation, major
& higher marketing investment in dollar value meals made McD's the growth leader in its competitive
segment for 2 years thereafter.
L'0real
Developed models which measured the ROI across 12 different "Celebrity Spokespersons" in L'Oreal
Commercials. Recommended reducing number from 12 to 5 Celebrities, leading to growth
improvement from +3 to +5%.
Hyatt Hotels
Developed SEI to quantify measure of "customer satisfaction" derived from measures of Trip Advisor
hotel reviews across 300 different properties. This lead to a 5% improvement in customer satisfaction
in subsequent year and a +6% growth in total bookings
AT&T
Identified and quantified impact from the launch of iPhone. By identifying which ad copy messages
were most effective, AT&T managed to increase it's wireless telecom market share from 28 to 30%.
Johnson and Johnson
Developed analytic system for measuring and evaluating ad copy for Splenda brand. Enabled brand to
reduce ad production from 8 to 4 commercial executions, saving $6 million
41
42. Global Analytics Partners
37
Global Analytics Partners is a consortium of advanced analytics, marketing technology
& strategy firms bringing together extensive global experience in all phases of marketing
science, decision support & advanced analytics. Collectively, we have the scale and the
tools to assume any challenge & have over 150 years of direct experience covering over 40
International markets
43. Bangalore, IN Office:
No. 141, 2nd Cross, 2nd
Main,Domlur, 2nd Stage, Bangalore
560071Phone: +91 80 40917572,
+91 80 40916116
info@therainman.in
Contact Us US Office:
Suite 100, 1780 Chadds Lake Dr, NE
Marietta, Georgia, 30068-1608
Atlanta, USA
mjw@bottomlineanalytics.com