Know What People Are Interested In. Not What They Say
Surveys capture what people say. Markets move on what people do.
MyTelescope is an AI platform that measures market interest—a behavioral signal built from how people search, read, and talk across the open web. It’s not a poll. It’s the demand signal in the wild.
Why this matters
Budgets need proof. Leaders must show that marketing moves business outcomes.
Stated intent is biased. Question framing and recall distort reality.
Behavior leads revenue. When interest rises at scale, sales often follow—if brands show up.
Proof over promises
We validate the Market Interest Index against hard outcomes. Across categories, we observe strong, repeatable relationships between market interest and revenue. For example:
Marriott: r = 0.80 (multi-year monthly)
Sheraton: r = 0.78
Different categories show different lags and strengths, but the pattern is durable: when market interest moves, money tends to move.
Want the full validation note and brand list? Contact us—happy to share methods and stats.
How the signal is built
Behavioral inputs: aggregated, privacy-safe indicators of real activity (e.g., search intensity, content consumption, public conversation).
Modeling: the platform measures, normalizes, and de-noises signals for seasonality, platform shifts, and exogenous spikes.
Attribution-safe: market-level measurement—no user tracking.
Where “interest, not opinions” changes decisions
Forecasting & planning: spot inflection points early and plan to ride the slope.
Budget defense: show the correlation/lag to revenue; replace “trust me” with evidence.
Category strategy: act when the category lifts, not just your brand.
Competitive moves: track share of market interest to anticipate shifts in mental availability.
Creative validation: if interest didn’t move, change the work or the channel.
Quick playbook
Set the baseline: Pin your last 24 months of market interest for your category and key brands.
Identify leaders/laggards: Who gains interest share when the category lifts?
Quantify the lag (monthly): Compute Pearson correlations at 0–3 month offsets and pick the best-fit lag (often 1–3 months).
Align spend with the slope: Increase investment when interest is rising; protect base when flat; test hard when falling.
Report with proof: Plot interest and sales by month on the same chart and annotate the best-fit monthly lag.What this is not
Not a replacement for all research. Keep qual for insight and quant for sizing. Use market interest to lead timing and confidence.
Not a vanity metric. If the signal doesn’t correlate to outcomes, we flag it or fix it.
What good looks like
Hotels: interest tracks revenue cycles with strong correlations and clear lags.
Beverages & FMCG: early category signals help winners build mental availability at the turn.
Consumer tech & mobility: fast cycles make interest spikes visible days before sales pulses.
The headline you can stand behind
Know what people are interested in—not what they say.
See interest rise before the quarter ends, and act faster than rivals waiting on last month’s survey deck.
Next step: We’ll map your last 24 months of market interest to your sales and show the lag, the correlation, and the playbook. If it isn’t actionable, we’ll say so. If it is, you’ll have the chart that defends your budget and guides your next move.
Transparency: Insights are generated by MyTelescope AI using aggregated, privacy-safe signals; correlations computed via Pearson correlation on multi-year monthly data.