In most cases you already have the data.
But, it’s on your servers, in the cloud, across multiple databases, and in Excel spreadsheets.
So, how do you use that information to identify the prospects who are most likely to become your best customers?”
There are three main challenges.
- Processing billions of records
- Normalizing data from multiple sources
- Keeping costs under control
Processing Billions of Records
MQ&C uses the Alteryx platform for very-large-database management, which gives quick and meaningful access to big data, speeds development of cloud-based databases, and efficiently handles all forms of data from multiple sources.
MQ&C holds licenses with many data providers and combines that data with the client’s proprietary data to develop predictive models that can be applied across a wide variety of marketing channels.
Our Chief Analytics Officer is an Alteryx ACE, a title held by only 24 worldwide who are certified as the best of the best. We combine his technical expertise with strategic insights to turn big data into actionable and profitable advertising campaigns.
Normalizing Data from Multiple Sources
With access to so many different types of data, we can figure out exactly what attributes of a prospect indicate that they will be a high-value customer. Let’s look at an example:
If you’re targeting a 30-something adult who makes $75,000 a year and has children, that sounds specific enough. Right? Well, we like to dig deeper. Age, marital status, home ownership, number of children, age of children, technical savviness, just to name a few. But those barely scratch the surface. Because the not-so-obvious data points can be very enlightening: NASCAR or golf? hip-hop or opera? CNN or Fox? Buick or BMW?
First, we run a massive analysis where we look at your customer database, and attach as many of these attributes to all your customers. Then we look at which attributes actually predict who will buy. Then we attach the same attributes to your prospect database. Now we can see, based on your best customers, which prospects are most likely to buy.
Keeping Costs Under Control
We take it even one step further, because with access to dozens of databases, once we know which attributes are most important, we can then choose the lowest cost source for that information.
With access to so much data, we can maximize their predictive value while minimizing usage costs.