Welcome to the biggest sandbox in the history of marketing.
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The Data Explosion
Web Analytics Marketing Automation
CRM
Engagement Channels Ecommerce Offline
Transactions
Surveys & Forms
Publishers & Partners
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Marketing data tech
Created by Scott Brinker @ChiefMarTec
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Marketing data tech
Created by Scott Brinker @ChiefMarTec
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Marketing data tech
Created by Scott Brinker @ChiefMarTec
Own, store & manage your own data.
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The Marketing Data Lake
The Marketing Data Lake
Franz Aman & Anish JariwalaISBN 978-0-9976012-0-6
Franz Aman & Anish Jariwala
How a new generation of marketing analytics (and a Big Data mindset) changes… absolutely everything.
Most marketers have never been able to answer the simplest questions about their activities. Questions like, “What’s working?” and “How much revenue have we created?”. But very few teams have been able to overcome the considerable obstacles to this kind of visibility and accountability. The Marketing Data Lake is about one team’s pioneering efforts to tackle this critical marketing challenge. It’s also about a powerful new idea for connecting the dots of marketing, integrating your most important data across your marketing applications and answering the simple questions that marketers have struggled with forever.
Franz Aman Anish Jariwala @ Informatica
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Data Warehouse
Data Lake
Data Types Structured Un- or Multi-structured
Database schema
Schema-on-write
Schema-on-read
Cost Expensive Low-cost
Agility Low High
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Data Lake
Analytics
Visualization
Personalization
Campaign Management
AdTech
Channels
Website Modeling
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Data is not an end in itself.
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Data is not an end in itself.
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Data is only useful if it helps us generate insight.
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Data is only useful if it helps us generate insight.
To guide strategy To shape action To inspire content
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Insight is a non-obvious understanding about your customers…”
Paul Laughlin, IoDM
“
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Data: People feed their pets twice a day
Kevin Davis, DDB
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Observation: They tend to feed them at breakfast and dinner
Kevin Davis, DDB
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Insight: People feel guilty about eating in front of their pets.
Kevin Davis, DDB
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“Ahi tuna on brown rice with carrots, tiger prawns, egg, garlic, and kale in ahi consommé”
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“Ahi tuna on brown rice with carrots, tiger prawns, egg, garlic, and kale in ahi consommé”
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Data Insight Content
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Leap 1 Leap 2
Data Insight Content
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Turning data into insight. Five approaches.
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1. Start with a single data point
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“Only 2% of women consider themselves beautiful.”
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Ads • Videos • Workshops • Sleepover Events • A Book A Play • Research Studies • A Touring Exhibition
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One insight.
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2% of women think they’re
beautiful
Data The $3 squillion beauty industry
is built on an unrealistic ideal
that makes women unhappy.
Insight Content
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2. Segment your customer base
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One moribund brand.
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One content explosion.
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One content explosion.
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One content explosion.
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One content explosion.
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“Dollop-able”
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Segmentation releases relevance.
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3. Make surprising connections
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Kids spend less than an hour a day outside.
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Weird connections between data sets can spark insights.
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4. Watch how data changes through the customer journey
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The Data-driven Mother’s Journey
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Gather data to help map content to journey stages.
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5. Think small
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• Start with a single data point. • Segment your customer base. • Make surprise connections. • Map insights to the customer journey. • Think small.