Demand Intelligence analyses changes in observed search and contextual interest in a category, brand or product. It can highlight seasonality, acceleration and regional differences. An interest index is not a count of patients or sales; planning conclusions should be checked against distribution, competitive activity and purchase data.
How it works
- 01Define category terms
- 02Collect comparable periods
- 03Identify seasonality
- 04Validate through media and measurement
Three coordinates for understanding interest
Make comparisons consistent
Use a fixed category, brand set, geography and comparable time windows. Search share is not market share.
Apply to media planning
Seasonal growth can guide earlier reach; a peak can guide frequency. Form a testable KPI for each hypothesis.
Connect to purchase evidence
Interest trends complement purchase data and Sales Lift but do not replace either. Research releases should explain sources and limitations.
From observation to a testable decision
Signals behind the demand picture
Available category, brand and competitor interest signals reveal topic shifts, seasonality and geography. The analysis explains not only that interest changed but what changed, where and relative to which comparison.
Three comparison levels
First assess the category and the start of its season. Then compare brand and competitor attention. Finally compare regions and time windows. Definitions and periods are fixed so charts remain comparable.
How it changes media planning
Predictable seasonal growth can justify building reach before a peak. Regional patterns inform budget allocation, emerging topics suggest creative tests and competitor movement identifies attention gaps. Each decision has a measurable KPI.
What the brand receives
The output includes category trends, brand comparison, seasonality, regional findings and testable media actions. Purchase data or Sales Lift are added when the question concerns actual sales.
Limitations
Interest is not disease incidence, packs sold or brand revenue. Results depend on source coverage and normalisation.
Questions
Can Demand Intelligence predict sales?
Interest can inform a forecast hypothesis but is not sales. Financial forecasts also need purchase history, distribution, price and promotion data.
How is an interest index different from market share?
The index describes observed activity in selected digital sources and method. Market share is based on sales. One cannot be substituted for the other.
Can regions and seasons be compared?
Yes, when category definitions, sources, windows and normalisation are consistent. Coverage differences are documented.
Does it work for a new brand?
Yes. Category, adjacent-topic and competitor trends can guide initial regions, season and messages. Campaign data can refine the picture later.
Can campaign impact be seen in search interest?
A time-series change can be examined but coincidence does not establish causality. A preplanned comparison is needed; purchase impact is tested separately with Sales Lift.