Why Targeting Smart
Automobile Service Centers Case Study - putting you in the driver's seat.
Stand Out, Be Found, Drive Results with Targeting Smart
Boost your brand awareness and reach your precisely targeted audience with our massive consumer database and cutting edge digital ad delivery technology.
PREFACE: Over the years, there have been numerous case studies between Targeting Smart and automotive industry clients that we could have been cited.
While all are equally important in the own right, we've chosen the Automotive Service Centers because it is the easiest to comprehend.
The Problem Statement
Most auto service centers do not possess the tools and expertise to thrive in today's digital landscape. Targeting new customers is extremely foreign and daunting.
With Targeting Smart we can provide small and medium-sized auto service businesses with cutting-edge digital advertising solutions. Our massive vehicle information database and advanced targeting capabilities can help them reach the right customers and drive business growth.

The Collaborative Journey
The first major step in crafting a digital-driven ad campaign for any auto service center is to learn about their core business (what they do well), what they want to accomplish, and their ad budget.
IMPORTANT NOTE: Targeting Smart has access to the largest vehicle database in the United States.
Reach nearly 200 million auto owners nationwide with our Automotive Database. Every record contains a VIN from which detailed vehicle-related information is derived including year, make and model.
All records are multi-source verified to ensure accuracy. This enables our clients to reach known vehicle owners by make, model, year, mileage and more. Our multi-sourced proprietary database is 100% marketing compliant and contains vehicle ownership records that are as recent as this year. The database is fully updated every month and built from tens of millions of privately sourced vehicle transaction sources including sales and service data, auto warranty data and aftermarket repair facilities.
The Solution - Case Study
This approach effectively addressed the client's need to target two distinct customer segments:
- Toyota Owners: The first campaign specifically targeted Toyota owners with messaging and visuals tailored to their needs, highlighting expertise in Toyota repairs. This likely resonated with Toyota owners who are looking for specialized service for their vehicles.
- General Vehicle Owners: The second campaign targeted a broader audience of car owners with messaging that emphasized general repair services for all makes and models. This ensured that the client could also attract customers outside of their Toyota specialization.
Key Benefits of this approach:
Increased Relevance: By tailoring the messaging and visuals to each target audience, the campaigns were more likely to resonate and drive engagement.
Improved Efficiency: Separate campaigns allowed for optimized budget allocation and performance tracking for each target segment.
Enhanced Brand Positioning: The Toyota-specific campaign helped establish the client as a specialist in Toyota repairs, while the general campaign broadened their reach and appeal.
Additional Considerations:
Data-Driven Targeting: The success of this approach relies on accurate targeting data. Targeting Smart likely leveraged their extensive database of vehicle information to ensure the ads reached the right audience segments.
Creative Differentiation: Using distinct graphics for each campaign helped further tailor the message and avoid confusing the target audiences.
Performance Tracking: Monitoring the performance of each campaign separately allowed the client to identify which segments were most responsive and adjust their strategy accordingly.
This dual-campaign approach demonstrates how Targeting Smart can leverage its expertise and technology to deliver customized solutions that meet the unique needs of each client.
IMPORTANT:
A word about smart digital-driven consumer targeting
Precision in digital advertising requires a delicate balance. While our vast database empowers you with deep consumer insights, over-targeting can limit your reach.
Our experts work closely with you to find the sweet spot – maximizing your reach while ensuring your message resonates with the most receptive audience; something social media providers (for example Google Ads, LinkedIn, and others) can't perform with their automated tools.
Deep Dive Analysis
Deep Dive Analysis
Deep Dive Analysis
Selectable Database Field Attributes
GEOGRAPHY Street State County City Postal Code MARITAL STATUS, AGE AND LIFESTAGE Gender Marital Status Year of Birth Full Date of Birth Age (banded) Partner’s Year of Birth Partner’s Full Date of Birth Individual’s Lifestage–Age Driven Household Level Lifestage–Age Driven Individual’s Lifestage–Family Status Driven Household Lifestage–Family Status Driven Young Adult Still Living at Home Number of Young Adults Still Living at Home PRESENCE OF CHILDREN Parent Status Dependent Children in Household Number of Children at Home (0-21 Years) Number of Children in the Household Aged 00-10 Number of Children in the Household Aged 00-16 Number of Children in the Household Aged 11-16 Number of Children in the Household Aged 17-21 Child at Home 0-4 Years Old Child at Home 5-7 Years Old Child at Home 8-10 Years Old Child at Home 11-16 Years Old Child at Home 17-21 Years Old Age of Eldest Child Age of Eldest Child in Household Age of Youngest Child Age of Youngest Child in Household Children’s Year of Birth HOUSEHOLD COMPOSITION Head of Household Indicator Household Size–Number of Adults in Household Total Household Size (Adults and Children) Summary Household Composition Detailed Household Composition HOME AND PROPERTY Home Ownership Status How Many Times Homebuyer (1st, 2nd, 3rd+ Home) Year Moved to Address Length of Residence (Banded) Month Moved into Current Home Year Current Household Moved Into the Address Household Length of Residence (Banded) Type of Property Number of Bedrooms Date Home Built OCCUPATION AND EMPLOYMENT MEASURES Individual’s Occupation Partner’s Occupation Individual’s Employment Status Partner’s Employment Status Self Employed Partner is Self Employed Run Business From Home (You) Run Business From Home (Partner) Individual or Partner is Professional/Manager Individual or Partner is Educational/Medical Individual or Partner is Office/Clerical/Shopworker Individual or Partner is Craftsman/Tradesman Individual or Partner is Manual/factory worker Individual or Partner is Self Employed Individual or Partner is Housewife Individual or Partner is Retired Individual or Partner is Student Number of Students in Household INCOME AND AFFLUENCE MEASURES Combined Annual Household Income Equivalised Income Equivalised Household Income Indexed to US Average Net Household Income Per Week (Banded) Net Household Income Per Week Indexed to US Average Discretionary Household Income Per Week (Banded) Dual Income No Kids Yet Affluence Ranking Household Affluence Ranking Lifestage by Affluence Household Level Lifestage by Affluence Household Socio Economic Classification Individual Has an Earning Occupation Partner has an Earning Occupation Incomes Across Individual and Partner Number of earners in the household Proportion of Adults Earning Number of Unemployed in the Household Proportion Adults Unemployed Number of Non-Earning Adults in Household Household Employment Status (Based on Household’s Primary Couple) Pensioner Status (Based on Household’s Primary Couple) LIFESTYLE–REGULAR LEISURE INTERESTS Bet on Horse Racing Book Reading Charities/Voluntary Work Crossword Puzzles Current Affairs Cycling Do-It-Yourself Eating Out Fashion Clothing Fine Art/Antiques Football Foreign Travel Further Education Gardening Going to the Gym Going to the Pub Golf Gourmet Cooking Fine Foods & Wines Grandchildren Health Foods Hiking/Walking Household Pets Jogging/Physical Exercise Listening to Music National Trust Personal Computing Prize Draws & Competitions Religious Activities Snow Skiing Theatre, Cultural/Arts Events Vitamins/Food Supplements Wildlife/Environmental Concerns Non Smoking Household Cultural Pursuits Interest level Entertainment Interest level Animal/Nature Awareness level Outdoor Pursuits level TRAVEL Take European Holidays Take USA Holidays–Ranked Likelihood Take Rest of the World Holidays–Ranked Likelihood Foreign Travel as a regular hobby Snow Skiing as a regular hobby | NEWSPAPER READERSHIP Quality Newspaper Readers Mid-Market Newspaper Readers Popular Newspaper Readers Financial Times TECHNOLOGY Have a PC in the Household Have Internet Access at Home Have Internet Broadband Personal Computing as a Regular Interest Games Console Digital Camera Mobile/Music Streaming Device Have Flat Screen TV Have HD TV Pay to View TV Subscription Cable TV Satellite TV Mobile Phone Mobile Contract Payment Type (Contract/Pre-Pay) Household Technology Ranking Consumer Electronics Audience Segmentation (Spend on Technology and Motivation to Buy) Telecoms Audience Segmentation (Spend on Communication Services and Devices and Motivation to Buy) AUTOMOTIVE Motorist Bought a Car Under 3 Years Old SMMT Car Classification Age of Car Bought Car New/Used Number of Cars in Household Car Fuel Type (Petrol/Diesel) Annual Mileage INSURANCE RENEWAL Car Insurance Expiry Month Buildings Insurance Expiry Month Contents Insurance Expiry Month Changed Home Insurance Provider in Last 3 Years Level of Motor no Claims Discount FINANCE AND INSURANCE Have a Mortgage Individual/Partner has Personal Loan–Ranked Likelihood Personal Loan Individual/Partner is Credit Card Holder Household Credit Card Ownership Number of Credit Cards Have Visa/Master Card Have American Express Card Have a Store/Shop Card Have a Debit Card Private Pension–Ranked Likelihood Private Pension Regular Savings Plan–Ranked Likelihood Regular Savings Plan Child Savings Plan–Ranked Likelihood Child Savings Plan Unit Trusts/High Interest Investments Own Stocks/Shares Have an ISA Investment Activity Ranking Household Level Investment Activity Ranking Life Assurance–Ranked Likelihood Life Insurance Private Medical Insurance–Ranked Likelihood Private Medical Insurance Accident Insurance–Ranked Likelihood Accident Insurance Funeral Plan–Ranked Likelihood Funeral Plan Insurance Activity Ranking Household Level Insurance Activity Ranking Will CHARITY INTERESTS AND ACTIVITY Charities/Voluntary Work Charity Donor Ranking Household level Charity Donor Ranking Donate to Environmental/Animal/Wildlife Causes– Ranked Likelihood Donate to Animal Pet Welfare Donate to Environmental Causes Donate to Wildlife Care Donate to Global Causes–Ranked Likelihood Donate to Disaster Relief Donate to Third World Donate to Other Causes Donate to Local Causes Donate to Children’s Welfare Donate to Help the Elderly Donate to Medical Research Donate to Disabled/Handicapped Donate to Cancer Research Donate to Help the Homeless METHOD OF DONATION Contribute to Charity in the Street/at the Door Contribute to Charity by Post–Ranked Likelihood Contribute to Charity by Post Contribute by–Direct Debit Contribute by–Internet ENVIRONMENT Environment Friendly Product Levels Recycled Product Levels Green Status–Ranked Percentile CHANNEL BEHAVIOUR Probability to Buy Groceries Online–Often Probability to Buy Groceries Online–Sometimes Probability to Buy Groceries Online–Never Probability to Buy Insurance–Online Probability to Buy Insurance–in shop Probability to Buy Insurance–by phone Probability to use Internet for–Email Probability to use Internet for–Google Probability to use Internet for–eBay Probability to use Internet for–Weather News Probability to use Internet for–Price Comparison Probability to use Internet for–Social Networking Probability to use Internet for–Messaging Probability to use Internet for–Gambling/Betting Probability to use Internet for–Games Playing Probability to use Internet for–Paying Bills Probability to Research Tech Prod–Online Probability to Research Tech Prod–in shop Probability to Research Tech Prod–from Catalogue Probability to Buy Technical Prod–Online Probability to Buy Technical Prod–in Shop Probability to Buy Technical Prod–via Catalogue Probability to Use Mobile Phone for–Internet Probability to Have Freeview TV Probability to Have Satellite TV Probability to Have Cable TV Probability to Read News Online–Often Probability to Read News Online–Never Probability to Read News Online–Sometimes Probability to Book Holiday via–Internet Probability to Book Holiday via–Agent Online Purchase Frequency Online Behaviour Segments MAIL ORDER Shopping by Catalogue Interest Mail Order Frequency GROCERY SHOPPING Main Shopping Weekly Grocery Spend CHANNEL PREDICTOR Preference to Receive Marketing Communications via Email Preference to Receive Marketing Communications via Direct Mail Preference to Receive Marketing Communications via Telephone Preference to Receive Marketing Communications via Text Preference to Receive Marketing Communications via Social Networking Channel Preference Mix Segments |