In principle, Findologic is a search service for online shops. I.e. the supplied modules primarily search the products of your shop, but not the content (e.g. imprint, blog posts, ...). However, this can be adapted.
If there is a manageable number of content pages (general terms and conditions, imprint, contact, ...) which are to be found for the most important search terms defined by you, then a solution via landing pages is the right choice.
If a not estimable number of contents is to be searched actually, this can be achieved by means of adjusting the export. Proceed as follows:
Adjustments of the export:
Each entry – whether product or content page – must have a unique ID in the export. We recommend providing the IDs with a prefix, e.g. "blog_123", "info_456", …
Similarly, the data records must have a corresponding group parameter. items e.g. "item", blog posts e.g. "blog". This also makes it possible to restrict the search results to certain types of hits.
Leave the price column for content empty.
Under this link you will find detailed documentation on exporting to CSV and under this link to XML.
Selection of hit types
In future, search queries should include the group parameter of your items (e.g. "&group=item") by default. In addition, you should create links in a suitable place (e.g. above the filters) with which the group parameter can be changed (e.g. "&group=blog") and thus the corresponding hit types can be displayed.
Like products, their contents can also be provided with attributes and restricted accordingly using the Findologic filters.
Use the always up-to-date Smart Suggest developed by Findologic. With corresponding hookpoints, you can search the IDs for corresponding entries before outputting the results (example ID: "blog_*") and display them separately in Smart Suggest.
Further documentation on hookpoints.
Please note: The item data is retrieved by default from the table in which the item data is stored. If content contributions are to be displayed in the search result, please note that this information is retrieved from the corresponding database/database table in which the content contributions are stored.