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Tuesday, 26 March 2019 21:58

AASP/NJ's NORTHEAST 2019 Features Industry’s Favorite Speakers

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Craig Seelinger, Vision+ program manager for BASF, presents “Business Data, Knowing Your Unknowns.” Craig Seelinger, Vision+ program manager for BASF, presents “Business Data, Knowing Your Unknowns.”


At 3 p.m., Brent Betts of AP Digital presented “Expand Your Customer Base – Reach More Online Collision Repair Customers.” He began by identifying the challenges that shops face and acknowledging that many shops are skeptical about marketing because they’ve had a bad experience in the past. Betts then pointed out that there is a huge opportunity in the collision repair industry with more than 1.54 million Google searches for collision repair each month.


“The great news is that consumers are actively searching for your services,” Betts noted. “Think of your website as a lead-generating machine. It’s the second side entrance to your lobby, but your website works 24/7 and can handle unlimited customers at the same time.”


After providing insights on the best way to monitor analytics to ensure the company website is generating leads and working for the business as effectively as possible, Betts dove into the differences between free and paid searches, discussed the most effective digital platforms and explored the most logical uses for social media for business. He also explained the importance of using online videos to invoke an emotional response.


He ended by encouraging attendees: “Look at where you’re at now and figure out how to get where you want to be.”


Next, Craig Seelinger, Vision+ program manager for BASF, presented “Business Data, Knowing Your Unknowns.” He explained that his discussion would focus on avoiding what he calls the “knowledge fallacy,” the belief that everyone knows what you know, and encouraged discussion, questions and open-mindedness throughout his presentation.


He noted, “The data we’re going to talk about can actually change your life and the life of those who work for you. Your business doesn’t come with instructions, but knowing your unknowns can be like receiving instructions.”


Some characteristics of good data include accuracy, completeness, consistency, uniqueness and timeliness.


Seelinger then provided examples of bad data.


“False, inaccurate data will give you a false, inaccurate analysis,” he said. “Wouldn’t you rather know how bad things are instead of painting a rosy, inaccurate picture? With bad data, you have a mess on your hands. If you like making bad decisions, keep putting bad data in your systems.”

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