The Road Ahead w/ Vanguard’s Head of Digital Integration and Analytics – February 21st

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Preparing For Data Driven Success in 2018 and Beyond

Rusty Rahmer, DAA President Elect and Head of Enterprise Digital Integration and Analytics at The Vanguard Group, will share his perspective on the trends and trajectory of our digital analytics industry, the challenges of the next generation of analytics, and how we as practitioners can best prepare for personal success. Topics include, Journey Analytics, Artificial Intelligence, combining Quantitative and Qualitative Data, and Data Science.
Based on his successes at Vanguard, Rusty will then provide guidance as to how organizations can build more successful teams and processes focused on gaining better data-driven, actionable insights to drive competitive advantage and greater customer satisfaction.

About Rusty

Rusty-Rahmer
Rusty Rahmer, Head of Enterprise Digital Intelligence and Web Analytics at The Vanguard Group, is an experienced digital leader, with over 10 years of experience driving digital strategy, technology program planning, and delivery at Vanguard. Since 2013 Rusty has been leading Vanguard’s enterprise digital intelligence program and has since built and managed the firm’s Digital Intelligence Center of Excellence. Rusty’s expertise is centered in developing digital program strategy, inspiring business leadership to invest, and providing program leadership through organizational construction and operational transformation.

Location:

General Assembly – Downtown Seattle:  1218 3rd Ave, Suite 300  Seattle, WA 98101

Agenda

6:30 – 7:00 : Networking
7:00 – 7:45 : Presentation
7:45 – 8:30 : Networking
Food and refreshment will be provided to all attendees

Registration

DAA Member: Free
Non Member: $10

DAA Register Now

 

 

Data-Driven Customer Journey Maps: Urgent Care at MultiCare Health System

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As health care continues to improve customer engagement in an ever evolving digital landscape, MultiCare Health System developed a Customer Journey Map for their new Urgent Care business line following months of research and data gathering.

At January 16th’s Seattle Marketing Analytics Meetup, MultiCare’s Executive Director of Analytics and Digital Strategy, Ann Goldman and Director of Media and Digital Communications, Marce Edwards Olsen, will provide a high level overview of the Customer Journey Map process, as well as discuss the unique analytic and strategic opportunities in retail health.

For additional details and to RSVP, click below:

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Mastering Your MarTech Stack – January 9th’s LA Marketing Analytics Group

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Most CMOs today spend more on technology than many CTOs. With a new “shiny object” appearing daily, it’s hard to know where to focus. What AdTech/MarTech tools should you be using? What 1st, 2nd, 3rd Party Data will improve your marketing? How do marketers make sense of it all?

At January 9th’s LA Marketing Analytics Group,  Mark Osborne, Senior Director of Client Success at Conversion Logic, will share his strategic framework for evaluating current marketing challenges through the lens of potential technology solutions. Included, are interactive calculators for ranking current organizational readiness, comparing alternate solutions, and tracking your path to digital transformation covering many popular buzzwords and acronyms like CRM, DMP, attribution, automation, and more. After his presentation you’ll be able to create a strategic vision for your organization and prioritize marketing technology projects that will make the biggest impact, with the least effort, as quickly as possible.

Mark has spent his entire career in marketing technology, digital strategy, attribution and much more. Currently, he is writing a book titled “Mastering Your MarTech Stack: A guide to getting the most from customer data and marketing technology” which will release sometime in 2018.

Details:

Where:  General Assembly – Santa Monica (map)
When:  January 9th at 6:30-9:00pm
Cost: Free (Appetizers and beverages provided by eSage Group)

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Starbucks’ Nirvana – Nov 28 – Seattle Mktg Analytics Meetup

Rani MadhuraSr. Advanced Analytics Manager at Starbucks, will share with us details around Starbucks’ mission critical Digital Order Management Initiative. The initiative’s goal is to consolidate the Mobile and Café orders to improve customer wait time via creatively managed Order and Item Sequencing decisions.

She will also share on Starbucks’ Capacity Planning Initiative, including

1.  Insights derived from their integration of the cross-functional datasets from Asset Management, Labor Productivity and Store Level Transactional Data Systems

2.  Key Metrics identified to effectively manage inventory levels and dynamic labor allocation

Rani will finally discuss ROI, best practices and future considerations for both initiatives.

Don’t miss this one!!

RSVP Now

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eSage Group (http://bit.ly/2f0JdMj) is the organizer and sponsor for the LA (http://bit.ly/2nhl5GP) and Seattle Marketing Analytics Groups.

Blockchain- Transforming Marketing Attribution & Beyond – Nov 9th LA Marketing Analytics Meetup

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Blockchain is a hot topic these days! What is it? What does it mean for marketing and analytics?

Come to this month’s LA Marketing Analytics Group Meetup to hear Miguel Morales & Sam Kim, Co-Founders of Kr8os, give a crash course in Blockchain and then discuss its use in Open Attribution Modeling and Programmatic Affiliate Marketing.

Where:  General Assembly – Santa Monica (map)
When: November 9th at 6:30-9:00pm
Cost: Free (Appetizers and beverages provided by your organizer, eSage Group)


eSage Group  is the organizer and sponsor for the LA and Seattle Marketing Analytics Groups.

 

Guest Post: The Digital Transformation of Retail

By ShiSh Shridhar, WW Director of Business Intelligence – Retail Sector, Microsoft

You go shopping; let’s say it’s a national hardware store because you have a painting project you’ve decided to tackle this weekend. You have done your research online, chosen the paint and now you are at the store to pick up your supplies and get started. But, when you reach the section with the paintbrushes, you realize you’re not exactly sure what you need. You stand there for a moment trying to figure it out, and then you start looking around, hoping a sales associate will appear. And one does! She’s smiling, and she’s an expert in paints and yes, she can direct you to the brush you need — and reminds you to pick up some blue tape.

Shish 1

Shopping miracle?

No, shopping future. This kind of positive customer experience is one of the many ways that artificial intelligence (AI), sophisticated data gathering, and the cloud are being used to empower employees, bring consumers into stores, and shorten the path to purchase. These advancements help brick and mortar retailers compete with online retailers in today’s world. It’s the digital transformation of retail, and it’s happening now in ways big and small.

AI + Data = Retail Revolution

This transformation is driven by data, which today can come from any number of sources. In this example (a product called Floor Sense from Microsoft partner company Mindtree), the data is collected from security cameras already in place throughout the store. The cameras capture footage of how people move through space, where they stop and what they do as they shop. The video feed is then analyzed using AI that has been trained to understand how a customer acts when he or she needs help. When that behavior is recognized, a sales associate with the right expertise is sent to talk to the customer and help the customer make a decision.

But a store’s proprietary data is only the tip of the iceberg. Today, there are millions of data points that are either publicly available or easy to purchase from companies like Experian and Acxiom. Retailers can combine that demographic data with their existing CRM data to model behavior and build micro-segmentations of their customer base. Insights from that narrow analysis allow retailers to personalize, predict and incentivize in ways that are far more accurate than ever before.

Putting data insights into the hands of employees

Already, that kind of analysis has helped make online shopping more productive with relevant, timely offers. The next step for retailers is to learn how to make data-driven insights useful to store employees, as in the hardware store example, so they can enhance the customer’s in-store experience. The data could come from a customer’s interactions with the retailer’s app, chat bots, social media, in-store beacons or Wi-Fi, all of which, when compiled, allows a retailer to make extremely accurate inferences about a given customer’s behavior.

Managed well, those insights help a store employee serve a customer better. Managed poorly, personalized targeting in-store has the potential to spook customers. To handle it well, retailers must do two things: First, any in-store tracking should be done through a consumer opt-in, with transparency about how the retailer will use the information. Second, the customer deserves a good value exchange; it must be clear to her how she is benefitting from sharing her information with the retailer, and how her information contributes to delivering her a frictionless shopping experience.

Using a customer’s digital exhaust to everyone’s benefit

As consumers explore purchasing options and develop their preferences using search tools, social media, apps, and in-store visits with a device in hand they leave behind a digital exhaust. Today, advances in AI, data aggregation, and the cloud allow retailers to collect that digital exhaust to generate a style profile of prospective customers, which can then be used to introduce those customers to other products they might like. In this so-called phygital world — where the physical and digital overlap — retailers can combine data from multiple places to make inferences that will help them sharpen their marketing approach. The techniques are at hand — now, it’s up to creative retailers to find innovative ways to use those insights to inspire their customers, and shorten the path to purchase.

This article was originally posted on Independent Retailer.

Marketing Attribution Preparedness

As a digital marketer, you have almost endless data at your fingertips. If impactful marketing attribution is your objective, you don’t need it all – just the right data: User Identifiers, Timestamps, Media Data, and Channel Data. Gather (and govern!) these four types of data to allow your attribution efforts to tell your story effectively.
-Alison Latimer Lohse, Co-Founder and Chief Strategy Officer, Conversion Logic

On August 1st, I had the pleasure of hosting Alison Latimer Lohse at eSage Group’s monthly L.A. Marketing Analytics Group event in Santa Monica, CA.  Alison took us through the full continuum of marketing attribution from:

Why Do Attribution: The marketing ecosystem is comprised of billions of different possible permutations of target audience touchpoints due to available marketing channels and tactics. Following the customer journey across this vast ecosystem to the point of conversion is challenging.

Attribution Determining Causality: Marketing attribution is the equivalent of determining causality. Conversion Logic focuses on advanced attribution: holistically measures points across all media stimuli in order to give credit where credit is due.

Marketing Channels: On an average over 90% of marketers said they used three or more channels currently, and a significant 39% said they will use more channels in 2 years. 6 on an average, and the number of available channels is on the rise. The good news: the trend is towards portability and accountability.

Marketer’s Questions to Consider: Credit where credit is due, Cross-channel impact, Identify waste and opportunities for scale, Find customers more efficiently, and Simulate investment strategy

Available Methodologies:

  • Last Touch: 100% credit to the last touchpoint leading to conversion
  • Rules/Heuristics: Rules used to allocate credit to each channel for conversion based on sequence, weighting etc.
  • Vendor Reporting: Publisher provides metrics on how media performed
  • Statistical Model: Statistical approach to allocate credit to each channel / touch-point (linear or logistic regression)
  • Machine Learning Predictive Ensemble: Ensemble methods use multiple algorithms to obtain better predictive performance.

Approaches to Marketing Measurement:

  • Media Mix Modeling (MMM)
  • Cross-Channel Modeling
  • User Level Attribution

Assess Attribution Readiness:

  • Identity: Know your objectives and align across the business
  • Alignment: Executive Buy In, Cross functional Champions, Ownership
  • Organize: Be conscious of how your mar-tech systems work together, make sure you can track all conversion data, create consistent taxonomy and data structure

Alison was only scratching the surface of the available innovations and successes of a well-thought marketing attribution plan. One of the key takeaways for me was the part of her talk that covered Attribution Readiness and the need for businesses to take an honest look at their available data around marketing channels to assess whether or not they are ready to launch into attribution. Some of the important assessment tests that were talked about, include a checklist of items to be aware of.  I think they are important enough to leave you with them as parting food for thought. Enjoy!

Attribution Evaluation Checklist

 

Methodology
– Digital Fractional Attribution Methodology
– Cross-Channel Modelling (Online & Offline)
– Modelling Transparency and Validation

Data
– Data Alignment & Reliability
– On-boarding and ETL Support

Partner
– Customer Service Level
– Implementation Time
– Partnership Cost

Product
– Side-by-Side Comparison of Last Click & Attributed Value
– Path to Conversion Analysis
– Detailed Optimization Insights & Recommendations
– Mobile Insights
– Customizable, Granular and Actionable Front-End