The Process: First, Dharamsi needed to go into the database and, field by field, figure out what was in it. “What we decided to do was get the ex-employee [who’d designed the original database] on the phone to try to figure out what fields were needed,” says Dharamsi. The hope was to save as much valuable data as possible. “There’s the terminology ‘garbage in equals garbage out’,” says Dharamsi, “but [data] is usually not garbage; you just need to tweak it and pull out the elements that are good.”
Once the publisher had determined which data was still usable, Quaero and the company went through an extensive discovery process to determine not only what the data was, but, for the purpose of constructing the relational database, how it planned to use it. It needed “to understand what it wanted to do with the system not just two years from now, but 10 or 15 years from now,” says Dharamsi.
From there, the existing data needed to be cleansed and standardized—an imperative step in building a relational database so that transactions that belong to the same customer record can be matched accordingly.
Outcome: Quaero had the company up and running on its new database in 90 days. The company is now able to access multiyear data and contact history; now it can base campaigns on behavior.
“Something I always preach,” says Dharamsi, “is that behavioral data can help you move to the next level.”
The company also has experienced improved reporting, as the previous reports from the legacy system had been far from accurate.
“[The database] is not just a black box anymore,” says Dharamsi. “We have a data dictionary and documentation so that if someone started tomorrow, they could read it and walk through it and get up and running right away instead of having to learn some antiquated language.”