As marketers, we want to be able to connect as much data as possible to a single customer, and these associations have to be accurate. What is the difference between Deterministic and Probabilistic matching and how does that impact precision vs. scale? Take a minute to watch and learn in our newest Marketing in a Minute!
(Marketing in a Minute Transcription)
We know that understanding the consumer is at the core of successful marketing.
- Who are they?
- What are their interests?
- Why are they going to engage with you or not? And,
- Where or How do they like to engage with you?
But, you can’t truly understand consumers, unless you can piece together all the information they’ve shared– across all personal IDs and devices.
And, how do you map all this data together to get that single view of the customer so you can provide relevant and consistent messaging?
Deterministic matching allows for an exact match between two pieces of data. But it’s challenging to find a single field common to two records, so you may sacrifice match rates in exchange for accuracy.
Probabilistic matching measures the likelihood that two records are a match by weighting several fields across records. Since not an exact match, here you may sacrifice some accuracy for reach.
Neither methodology is right nor wrong. For some advertisers, there is no substitute for accuracy. For others, close enough is good enough and maximizing match rates are paramount. Consider what you are trying to accomplish, consider the trade-offs and you will be able to determine which is right for you.