Discovering the Requirements – What analysis will I require?

In the last posting we looked at understanding your communication needs. We will now turn our attention to look at analysis and reporting, using the information gathered for campaign inclusions and exclusions to help with the identification of core analysis metric needs. This posting is the fifth instalment of the Discovering the Requirements series.  If you are joining the discussion now, you may want to start by reading the first posting.

Before looking at the analysis scenarios and reports required to be supported by your solution, a key item is to understand the difference between analysis and reporting:

• Reporting – Delivery of data into a structured fixed presentation, providing information on known measures at periodic intervals. For example, a campaign summary report, a KPI report, etc.
• Analysis – Providing insight into data, allowing interpretation and investigation of existing and proposed hypothesis on an ad-hoc basis.

Another way to look at this is that reporting should present information in a standard form and raise questions on the performance of the business. Analysis should enable those questions to be investigated and answered, or at least provide the reason behind the information presented in the report.

If we now look at analysis, a good place to start is to identify your current needs and how you use analysis to support your marketing activity, for example:

• Customer and activity analysis.
• Cross channel and product spend analysis.
• Churn Analysis.
• Campaign selections and segmentation.
• Campaign performance analysis.
• Responding to ad-hoc enquiries from the business.

Looking at each of these identified uses will provide a picture of:

• Who performs the analysis?
• How and what information is accessed?
• Type of analysis completed (Simple counts, cross tabulations, etc).
• Level of analysis (Customer, Email Address, Postal Address, Campaign, etc)

A similar exercise should then be carried out for existing reports to provide a high level view of current analysis and reporting.

To help gain a greater sense of current and future analysis a review of core analysis scenarios should be completed covering:

• Acquisition analysis (Lead time analysis, permissions, affiliate analysis, acquisition channel, etc).
• Conversion analysis (Looking at the customer journey and how the customer moves through the key life stages with your company).
• Cross Sell analysis (Review of product purchase type, price bands, additional add-on products/services, etc).
• Retention analysis (Review of customer churn, customer profiles, lifetime value, etc).
• Customer Development analysis (Product type purchase lifecycle, marketing communications, permissions, RFM, etc)
• Campaign effectiveness (Campaign response rate, average order value, open rate, click through rate, cost per order, etc).

For each of the analysis scenarios the key metrics and data used should be identified. For example to complete the acquisition analysis for an insurance business the following key pieces of information may be utilised:

• Originating media code (source) of individual.
• Number of quotes by individual in first 6 months/12 months/etc.
• Customer age.
• Customer postal address (Postcode).
• Number of failed applications.
• Number of days from quote to policy.
• Marketing permissions.
• Preferred channel of communication.
• Number of cancellations.
• Policy monetary value.
• Number of individuals in household with an active policy.

A similar exercise can then be performed for current and future reports, ensuring the following key information is obtained for each report:

• Report name and summary description.
• Filters which are required to be applied to the report (e.g. Campaign, Year, Season, Channel, etc)
• For basic line listing type reports (e.g. Campaign Effectiveness Report) an understanding of row and column reporting variables is required, to define which information is going to be used in presenting the report.
• For management type reports (KPI report) an understanding of each key piece of presented information is required, to define which information is going to be used in presenting the report.
• Details of any summary information presented.

A complete picture of required data elements can be built using this information and the details obtained during the review of communication needs. This can then be used to review each item to see if this is provided directly from source data or is an analysis metric, which will require the definition to be understood. For example, looking back at the acquisition analysis for an insurance business highlighted earlier, the following definitions could be identified:

• Originating media code of individual – Provide from source data on quote and policy.
• Number of quotes by individual in first 6 months – Derived from the customer first touch point date and knowing which quotes are linked to which individual.
• Customer age – Derived from the customer’s date of birth (Note: This may need to be grouped into age ranges for reporting/analysis purposes).
• Customer postal address – Provided from source data on the customer.
• Number of days from quote to policy – Derived from the customer’s first quote issue date to their first policy start date.

After completing this exercise you will have a complete inventory of required metrics and underlying data to support campaigning, analysis and reporting needs. This should be validated during the review of data required in the Customer Marketing solution, which I will cover in my next posting.

Please join me next week when I will discuss the data required to underpin your Customer Marketing Solution, reviewing how this is identified, understood and used to help build the solution. (Week 6: How much data will I need?)

If you have any further questions or would like support / guidance in discovering or defining your Database Marketing solution, please contact me through the BlacklerRoberts Ltd “Contact Us” page and I will be happy to discuss your needs. You can also follow @BlacklerRoberts on twitter for further insights.