Data-driven marketing and advertising campaigns yield a significantly higher return on investment (ROI) than traditional marketing campaigns. Such impressive results are made possible because data-driven marketing campaigns are based specifically on your business’s unique data footprint.
Effectively leveraging your existing customer data, sales data, marketing data, and prospect data requires a concerted effort with focus in three key phases:
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1. Data discovery: preparing and organizing your raw customer and sales data for analysis.
2. Modeling: choosing and performing the most appropriate type of analysis for your goals. Find out more about modeling here.
3. Application of the model: applying the results of the modeling phase via direct marketing, mass marketing, interactive marketing or other marketing methods in order to achieve the desired return on investment.
The first phase of any data-driven marketing campaign that MindEcology designs and executes involves data understanding, or data discovery. Data discovery is an important step in the internationally-recognized CRISP-DM methodology for database marketing. In a word, data discovery involves preparing your raw data so that it can be effectively manipulated for further analysis. The data discovery process itself is sub-divided into four steps: data acquisition, data description, and data quality assessment and data preparation.
Data acquisition involves locating and gaining direct access to your data, wherever it may reside. In the case of most organizations, data can reside in any number of organizational divisions, departments, databases and formats.
Once your data has been sources or acquired from various the various places where it “lives,” the various sets of data need to be integrated into one or more database tables or flat files.
Fortunately, compiling your data does not have to be a cost or resource-prohibitive undertaking. At MindEcology, we can make things easy by issuing very clear data requests at the beginning of a project. Upon request, we can even access your data temporarily via remote desktop login in order to help you properly export it for transmission to us.
Find out more about data acquisition here.
Once your data has been acquired, an initial data description must be performed so that we can gain deeper insights into the nature, organization and quantity of the data you have provided to us.
The data description step is akin to taking a tally of your data. We create both verbal and statistical descriptions of the data you have provided us. This position us to assess the quality of your data.
Find out more about data description here.
Data Quality Assessment
During the data quality assessment step, we take the necessary steps to determine how complete and usable your data is in its current state. There is virtually no data set in any company, local government, law/accounting practice, or not-for-profit entity that is 100% clean, accurate and complete. Typical issues with data quality include:
- Missing data
- Inaccurate data
- Misclassified data
- Data type errors
Fortunately, no matter how “dirty” or incomplete a data set may be, it can almost always be turned into a usable format.
Find out more about data quality assessment here.
The data preparation step is the culmination of the data discovery process. During this step, we directly improve the quality of your data through various preparation steps. Steps can include:
- Fill in missing values
- Realign data in proper fields
- Transform values to make them more manageable
- Codify values into categories
- Removing invalid records
- Reduce the size of large data sets through sampling
Find out more about data preparation here.
Typically, the Data Discovery phase is followed by our Predictive Modeling phase. We then implement our findings in the form of a marketing campaign via our full set of Marketing Services.
Contact MindEcology today to get started.
More useful links about our Data Discovery process: