A business group of a major integrated shipping and logistics company had many years’ worth of focus group market research covering varied topics from packaging preferences to drop-off locations stored in multiple formats in multiple locations (including a manager’s desk drawer).   Having a substantial investment in the research, fearing unnecessary duplication and knowing how much actionable learning was in the research, we were approached about finding ways to better store, search and access the research.  We designed and built a repository and accompanying multi-parameter search engine with results in context using AKTAV.

The marketing team had commissioned focus group research over a period of years (70+ focus groups per year) focusing on many different subjects among different customer demographics.  The raw data (questions, transcripts, videos, participant demographics etc.) and the analyses and reports for each wave were usually stored in shared documents.  The marketing team knew that it had a wealth of information that wasn’t being leveraged because of the lack of easy, context-driven access by those who could use it.

Using the AKTAV, the we built a repository and context driven search engine system that consisted of:

• An event module that captured descriptive information about each focus group (i.e., location, demographics, screening criteria, date and time, etc.) with a flexible hierarchy that allowed the building of waves, regions, etc.

• An asset repository that stored source documents and reports in their native formats (text documents, videos, audio, etc.)

• An upload module that uploaded the assets to the repository and captured descriptive information about the asset (i.e., format, keywords, type (i.e., transcript, research guide, etc.)) as well as tying it to a specific focus group and other assets (e.g., transcripts to videos). To make the system more powerful, in addition to keywords, for certain asset types, the upload module also further processed the file to allow for natural language search (non-keyword words and phrases).

• A search engine with multiple search options that could be combined (i.e., keywords; natural language; descriptors like location, demographics, wave, etc.; etc.)

• Ranked search results by relevance with search terms highlighted in sentence fragments to put the results in context; links to descriptors for both the focus group and the asset (e.g., videos, transcripts and reports); and links to the asset in the repository

• Streaming video and audio to view recordings of the sessions

The system provided the marketing team (and other stakeholders) with universal, context-driven, access to the research.