Is the data layer or the interpretation layer the bigger problem?

For most teams in 2026, the interpretation layer. The data is good enough. The synthesis on top of the data is thin. Investing in stacking, recency filtering, and one-paragraph interpretation per alert produces faster ROI than upgrading the underlying data feed.

How many alerts per week is the right volume?

20 to 60 high-conviction alerts per week for a typical mid-market team. Substantially more usually means the threshold is too low. Substantially fewer means the threshold is too high or the signal pipeline is undersourced. The volume should match what a rep can triage and act on.

How long does it take to fix a misreading team?

Two to three quarters for steady-state improvement. The first quarter installs the stacking, recency, and interpretation layer. The second quarter calibrates thresholds against observed outcomes. By the third quarter the system is producing measurably better conversion.

Why Most Sales Teams Misread Company Signals

91 percent of B2B marketers use intent data, only 24 percent report exceptional ROI. The gap is not the data, it is the interpretation. Most teams misread signals because the signal-to-action chain is broken in five predictable places.

The 24 Percent Gap

Subscribing to a feed and acting on it well are two different jobs. Most teams invest in the first and not the second. CRM data quality and alert volume reinforce the gap.

Five Common Misreads

Research as intent, singles as patterns, ignoring decay, missing the dark funnel, and skipping interpretation entirely.

The Corrections

Each misread has a cheap fix: signal stacking, corroboration thresholds, recency windows, passive intent monitoring, and one-paragraph interpretation per alert.

The Interpretation System

Four steps: stack signals, filter by recency, write a synthesis paragraph, attach the recommended action. The difference between a useless alert and a useful one is the synthesis layer.

Maintenance Discipline

Quarterly audit of signal-to-action chain, monthly data hygiene on contacts, and rep training through exposure keep the system honest.