|This research examines how data from passive digital tracking intersect with traditional survey data to deliver optimal insights. The authors’ quantify the value of social media engagement, visits to brand-specific websites, visits to 3rd party review websites and general search activity and compares and contrasts these influences between the automobile and two other products with varying purchase cycles.
- Big data seems like the Emerald City. Walk down the path to purchase with a spring in your step. But this is not reality. Big data is more like the man behind the curtain. It’s dream versus reality.
- We try to understand things COMPLETELY before we really start to use new things.
- We still don’t know what questions we can answer and what the value of the data is.
- Explored auto, smartphones, and pizza in tracker surveys, asked about purchase intent, loyalty, and social media habits for each, over 4 weeks. Also passively tracked computer for website useage
- Influence of digital media grows the closer to get to purchase and the growth is greater for more expensive purchases. Who’s going to do a big internet search on pizza, come on!
- Visits to review websites are much higher for auto compared to phones and particularly pizza. Opinions of a person I’ve never met and will never talk to is more important that a one million dollar marketing campaign
- Visits to brand websites are extremely important closer to the auto purchase, but local retailer and distributor was more important for smartphones
- Most people have no idea why they buy a car unless they sit with a psychologist for 15 sessions. You have stuff going on in your head far beyond “I like that one.” You can probably list 2 or 3 things but that’s not everything.
- Print, TV, Radio ad usage is stable over the purchase stage. Website usage increases over the purchase stage. We need to make sure the right stuff is available at the right time in the purchase cycle.
- You know ahead of time whether you’re going to spend 20 or 30 or 40k on a vehicle. Then we need to figure out where and how to get that car.
- Survey will say what WE say we are likely to buy. But digital data can say you looked at all these other cars too. Why didn’t you pick this one or that one?
- Also think about differences between what we said we did and what we actually did. People might not remember what they actually search for online and how long they looked at those sites. Inflation decreased over the tracking weeks and was far less for the pizza and far more for the car.
- Processing URLs is insane. There is no standard. Need a taxonomy for digital content so we can characterize what we want. It all needs to be put into a structure and coded. We’re not efficient at that yet.
- Theory, hypthesis, design, data. That was the old way and it was expensive and inefficient even though it had high value. Online model flipped that and we become more inductive, we made sacrifices, and did a lot of research just for the heck of it and figured out our hypotheses after the fact. Now we need a balance, need to move back to classical approach to research. Cannot go into this world on a fishing expedition anymore. This is a challenge.
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