making customer data actionable with predictive analytics in the automotive market
TRANSCRIPT
Using Predictive Analytics to Achieve
Relevancy and Improve Sales
DAN SMITH
CHIEF MARKETING OFFICER, OUTSELL, LLC
Dan Smith | CMO | Outsell, LLC | [email protected]
Dan Smith | Outsell | CMO | [email protected]
Consumer Expectations
Dan Smith | Outsell | CMO | [email protected]
Consumers Expect:
•An engaging brand experience
•On their own terms
•Via any (and all) of their devices
Dan Smith | Outsell | CMO | [email protected]
The Industry Challenge
Dan Smith | Outsell | CMO | [email protected]
In 2005, Shoppers would visit 4.5 dealerships within a 20 mile radius*
*Building A Groundbreaking Video Strategy Guaranteed To Sell Cars
Phil Sura & Peter Leto, presented at 2013 Digital Dealer Conference
TV Ads
Radio
Newspaper
Car Shopping Was Linear
Dan Smith | Outsell | CMO | [email protected]
Now more than 50% gather information 6 months prior to purchase.
In 2012, shoppers visited 1.4 dealerships within a 100 mile radius
It’s Not Linear Anymore
(2)
(1) J.D. Power & Associates
(2) Building Groundbreaking Video Strategy Guaranteed To Sell Cars
Phil Sura & Peter Leto, presented at 2013 Digital Dealer Conference
1
2
Dan Smith | Outsell | CMO | [email protected]
• Collectively, the ownership period currently stands at 4.75 years, up from about 3.2
back in 2002*.
• New vehicles = 6 years
• Used vehicles = 4.2 years
• Average service interval has increased over the past year from 140 days to 145
days**.
• Oil changes up to 13k miles
• Spark plugs up to 100k miles
• Increasing reliance on service prompts
Purchase and service intervals are at a record high
Source: *Polk Finds Average Age of Light Vehicles Continues to Rise, August 6, 2013, HIS
**DMEautomotive Research, September 4, 2013
Dan Smith | Outsell | CMO | [email protected]
The Case for Relevancy
Dan Smith | Outsell | CMO | [email protected]
Dear Ford,
Seriously? I own a Mustang. You know I do. I follow Mustang on Twitter and
liked it on Facebook. I've clicked through emails you've sent me to go search
your site for Mustang paraphernalia and badges, check out the current
model, and "customize" my dream Mustang (three times!). I've clicked
through Mustang ads (and Camaro ads, not that you'd know that). I've never
once expressed any interest in an SUV. Why on earth would you email me
about the Escape? It may be all new, with cool features and whatever, but
clearly I'm interested in sports cars, not sports utility vehicles. You may want
to reconsider your segmentation strategy. Thanks for thinking of me, though.
Source: DM News
?
Dan Smith | Outsell | CMO | [email protected]
Relevancy Matters:
72% of auto shoppers are open to influence prior to making a
purchase decision
52% said that ongoing dealer communications had a direct
influence on the purchase of their next vehicle
Targeted email prompted 28% of shoppers to begin their
vehicle purchase journey.
Digital Drives Auto Shopping; Google, November 2013
Dan Smith | Outsell | CMO | [email protected]
How to Get Relevant
Dan Smith | Outsell | CMO | [email protected]
Monitor Every
Customer Interaction
Detect In-Market
Shoppers
Missed Signals =
Missed
Opportunities
Relevance + Timing
= $uccess
Anticipate Service
Needs
Understand
Interests &
Preferences
Predict Behavior
and Measure
Loyalty
4-6 years is a long time. Analytics is the solution.
Dan Smith | Outsell | CMO | [email protected]
The power of Your Data
• Dealer data is rich but
underutilized
• DMS, CRM & Web
• Collectively dealers
maintain 10X more
customer data than
OEMs
Dan Smith | Outsell | CMO | [email protected]
What’s the Solution?
Dan Smith | Outsell | CMO | [email protected]
Predictive Analytics
The analysis of
current and
historical facts to
make predictions
about future
events
Dan Smith | Outsell | CMO | [email protected]
Get Smarter With Predictive
Analytics
• Gold standard for driving
relevance
• Requires a specialized skillset
• Could double your results
Dan Smith | Outsell | CMO | [email protected]
The “Pregnancy–Predictor” Model
Dan Smith | Outsell | CMO | [email protected]
Aggregate all online and
offline consumer
information
Use predictive analytics
to understand past and
present consumer
behavior
Relevant and timely
communications
• Multi Channel
• Integrated
Engaging each customer and prospect in a cross-channel dialog that
builds upon their past and current behavior
Goal: Effective Customer Engagement
Dan Smith | Outsell | CMO | [email protected]
Predictive Analytics & Business Intelligence
Business Intelligence
Reports, metrics, dashboards up to this point in time
User-driven to explore data and interpret results
Based on experience and gut-feel
Predictive Analytics
Automatically discover important patterns
Learn from historical data and create predictive models
Consistent, objective, efficient, fact-based
Deploying Predictive Models
Leverage current and historical data
Make predictions on current and future cases
Deploy to enhance outcomes
Reactive
Proactive
Dan Smith | Outsell | CMO | [email protected]
What are Predictive Analytics?
Predictive analytics employ a variety of techniques from statistics, modeling
and data mining to analyze current and historical customer data to develop
models that predict likely preferences, future events and next actions.
Why use Predictive Models?
• anticipate needs
• detect preferences
• improve message timing
• increase relevancy
• engender loyalty
• improve sales
Introduction to Predictive Analytics
Dan Smith | Outsell | CMO | [email protected]
© Outsell, LLC | Strictly Outsell Confidential
Predictive Analytics enables dealers and brands to
precisely target customers with tailored communications
based on their likelihood to:
• Purchase or Service within a given
timeframe
• Respond to an offer
• Defect to another brand
• Advocate for your brand
• Prefer a specific vehicle class, model,
feature or price point
• Spend a certain amount over their
lifetime
Predictive Analytics
Dan Smith | Outsell | CMO | [email protected]
© Outsell, LLC | Strictly Outsell Confidential
Propensity Value Preference
Defection Response In-Market
Typical Model Types
Example: Segment Intender
identifies customers who have high propensity to
purchase within a specific vehicle segment.
Example: Price Point
identifies customers who are highly likely to
prefer a vehicle within a specific price
range.
Combining models allows you to precisely target consumers with highly-relevant
messaging and offers.
Dan Smith | Outsell | CMO | [email protected]
Business Objective: I want to identify which consumers are in market for a
vehicle so I can target them with relevant and timely offers
In-Market Timing Model
• Customers/prospects/both?
• Purchase/Lease?
• Today/tomorrow/next month?
• Brand?
I want to predict which customers will purchase in the next 90 days
Dan Smith | Outsell | CMO | [email protected]
I have data (vehicle purchases, ROs, demographics, offers,
responses) from a variety of sources.
I’d like to predict the likely future behavior of a customer. I‘ll use
historic data that has examples of that behavior:
Age Education Marital Gender Occupation Historic Response to Offer
21 College Single Male Engineer Yes
23 HSgrad Single Male Administrator No
29 HSgrad Married Female Bus. Owner Yes
Build a model (find the patterns) then use the model to predict that
behavior for new records:
Age Education Marital Gender Occupation Predicted Response to Offer
24 HSGrad Married Male Engineer No
27 College Single Female Bus. Owner Yes
31 PhD Married Male Bus. Owner Yes
Developing Predictive Analytics Models
Dan Smith | Outsell | CMO | [email protected]
Business Objective: I want to predict which customers will purchase in the
next 90 days
Source: Outsell Insights
Analytical Framework
Cutoff
Date
1/1/2014
Decision Period
1/1/2014-3/31/2014
• Identify purchasers
and label as 1’s
• All other label as 0’s
Customer Behavior and Profile Data
5 years sales
2 years RO’s
24 months Clicks/Opens
- 60
months - 24
months
- 1
month
+ 1
month
+ 3
months
Dan Smith | Outsell | CMO | [email protected]
Source: Outsell Insights
• Every consumer has a unique “score” that captures the essence of
what is being modeled
• The “score” is essentially the “probability” of something happening
scaled in a predefined way
Example:
Customer 1234 has a score of 900 which translates to a
90% probability of purchasing in the next 90 days
Customer 1357 has a score of 600 which translates to a
60% probability of purchasing in the next 90 days
Output of Modeling Process
Dan Smith | Outsell | CMO | [email protected]
© Outsell, LLC | Strictly Outsell Confidential
Model scores can be combined to develop a
complete picture of consumer intentions
• Scores can be ‘layered’ to identify prospects who are:
• In-market
• For a specific type of vehicle
• With specific features
• And financed in a specific way
Targeting Power
Dan Smith | Outsell | CMO | [email protected]
Benefits of Predictive Analytics
Source: Aberdeen Group, September 2011
Dan Smith | Outsell | CMO | [email protected]
Case Studies
Dan Smith | Outsell | CMO | [email protected]
Consumer click behavior is one of the most valuable sources of data in
understanding consumer intentions and crafting targeted marketing
communications
45% of purchase likelihood within 90
days is explained by click behavior* *Opening an email, clicking on inventory, valuing trade-in
Source: Outsell
Timing Model Case Study
Dan Smith | Outsell | CMO | [email protected]
© Outsell, LLC | Strictly Outsell Confidential
Case Study: Analytics-driven Dealer Communications
Source: Outsell
• Customers that engage with dealer communications are
4x more likely to purchase from the dealer
• Over 50% of customers and prospects engage with dealer
communications within 6 hours of receiving a targeted
communication
• Customers engage with dealer campaigns 7 times before
coming in to purchase a vehicle
Dan Smith | Outsell | CMO | [email protected]
Questions & Answers
Contact Info
Full Name:
Company:
Job Title :
Email:
Dan Smith
Outsell, LLC
Chief Marketing Officer
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