Using Real-Time Data to Power Relevant Conversations

1. Getting to Now
Using Real-Time Data to Power
Relevant Conversations
Christian J. Ward
Chief Data Officer

2. When Will Then Be Now?
the best example of using real-time data I’ve found in film…
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9. Are Amount and Quality the Same?
The never ending struggle
between the amount of data and
the quality of the decisions we
can make with it.
(Technology vs. Marketing)
Not:
“How much do we keep?”
But:
“How much do we query?”
Keep it all!, But identify what you
need to query to achieve the
particular goal.
Prioritize your data, to each application and goal, focus on the question and use the best
data you can to answer it.
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10. What Can We Know?
What data can be known about each of us right now?
Where you are. What you ate for dinner last night.
When your flight leaves. What you read last.
Your income. Are you looking for a new job? Your next appointment.
Your NCAA bracket. Your social network. How far from home you are.
Who your biggest competitor is. Who you work for. If you are tired.
Your favorite food. Did your company grow or shrink last year? Where you were in the last hour.
What your company does. Where your rental car is. How long you slept last night.
Your age. The people you call, tweet, and text most.
If you like movies, fishing, video games, or PowerPoint presentations. Political ideology.
Who your most important relationship is. If you are married.
Where you were 6 months ago. Who you will most likely call in the next hour. How crowded this room is.
Who’s sitting next to you.
Priority depends on application or goal, but all of this data can get confusing and,
ultimately, unproductive.
Are we focused on the right things?
Is there a better way to find the answers?
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11. When Will Then Be Now?
Classic Models
• So what can we know now? From Then to Soon
• Both classic and “now” models offer
value and return
• But Now adds a completely new Then
element with powerful implications • transactions
• behaviors
• These elements, such as location and Now
• past social
proximity also give way to new Soon • monetary • location
elements, like direction, likely path, • visits • time Soon
and, eventually, need • snapshots • proximity • path
• context
• In addition to Then, Now, and Soon, • recency
• interest
• need
• openness
the ability to track data changes • openness
through time adds a completely new
capability…
• When Then and Now show change, Now Models
Soon becomes actionable… From Then to Now to Soon
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12. KNOW So Lo Mo
Right now… social local mobile
• your client is reading your catalog
• your transaction data is getting older Now.
• millions of mobile phones are “pinging” You’re looking at now,
sir. Everything that
• a table opened up at your favorite restaurant
happens now, is
• the cheapest gas in the area is 2 miles from here happening now.
• the highlight and glancee apps knows what you
have in common with the person next to you
• your customer is checking in at your competitor
• Infogroup is speaking to thousands of businesses gathering data
• Right now, data is changing, evolving, and triggering the next generation
of marketing and client engagement…
Knowing what happens Now redefines how data is Prioritized.
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13. Now Changes How Data is Analyzed
Transactional Behavioral Temporal Demographic
• There are many classes of data elements like these (HUBS of DATA)
• Storage, recall, query, and efficiency often limits our usage and creates massive IT
barriers that marketers can’t overcome (internally and externally)
• Further, getting a temporal view of this data, to see changes and triggers can require
massive infrastructure
• But much of that changes the closer our data gets to “NOW”
• Question: Which is more valuable?
Where your client was 6 months ago? - Or - Where your client is right now?
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14. Data Perspective & Priority
Typical Data Hubs:
• Transactional Transactional
• Temporal Temporal
• Behavioral Behavioral
• Demographic
• Social
• All the data is great, but
when it crashes into mobile
and social, the Now takes
precedence
• Selecting the elements that Demographic
matter becomes easier and
more useful
• If a customer or client is in a certain place, at a certain time, then linking the proper
offer, suggestion, content, or suggestion becomes drastically clearer
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15. Real-Time & Now Leads to Soon
Who What Where When
The people, person, The data on what The Location, business, The time it occurred in
business, phone, happened or what was or place, online or a scale that can be
identity measured itself offline related to other data
John may buy shoes at the Nike store next Tuesday.
• At any moment, data is typically in snapshot form and does not show the linkages of
time and place in a dynamic manner
• For many, the change in any of the above four element categories are separated and not
closely linked or reachable quickly (not Real-Time)
• The number and depth of elements in each category are often not prioritized, leading to
further confusion
• Lastly, who “John” is when he “buys” at the “Nike store” on “Tuesday” may not be
exactly who John is the rest of the time from a data perspective
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16. Christian J. Ward
Chief Data Officer
Christian.Ward@infogroup.com
www.infgroup.com
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