Most sales teams run a search, scan the top five results, and move on. They leave behind a wealth of analytical data that could tell them whether their query was strong, whether the results are worth pursuing, and where to focus their outreach. The search analytics sidebar exists to surface that data — eight tiles that together paint a complete picture of every search you run.
If you have already explored our Mission Control overview, you know that the analytics sidebar sits alongside your results in a sticky two-column grid. Each tile distills a different dimension of your search into a visual summary. Understanding what each one tells you — and what to do with that information — is the difference between running searches and running strategic prospecting campaigns.
This guide walks through all eight tiles, explains what each number and chart means, and shows you how to combine them into a practical workflow that improves with every search.
Tile 1: Quick Stats
The Quick Stats tile is the first thing you see — a bento grid of four numbers that give you an instant health check on your search. Before you scroll through a single result, these numbers tell you whether the search was productive.
- Total Results: The number of companies returned and successfully scored. A search returning 40+ results generally means your query was broad enough to capture the market segment. Fewer than 20 suggests a very niche query or a geographic area with limited coverage — consider broadening your search terms or expanding the location radius.
- Average Score: The mean deal score across all results, calculated from six weighted dimensions. An average above 55 is solid — it means the search surfaced companies that broadly match your intent. Below 45 usually indicates a mismatch between your query and what the scoring model considers a strong lead. Refine your search terms or try a different depth level.
- High Scorers (70+): The count of companies scoring 70 or above. These are your strongest leads — the ones most likely to convert based on their digital footprint, market presence, and relevance to your query. A good search produces at least 5-10 high scorers from a set of 40-60 results. If you see zero, your query may be targeting a segment where few companies have strong online signals.
- Search Quality Indicator: A composite signal drawn from the other three metrics. Think of it as a single thumbs-up or thumbs-down for the overall search. If this looks weak, do not waste time reviewing every result — iterate on the query first and run a fresh search.
The Quick Stats tile is your gate. If the numbers look healthy, proceed to the detailed tiles. If they look off, reconsider your query before investing time in the results. This single habit — checking the stats before diving in — saves experienced users hours of wasted review.
Tile 2: Score Distribution
The score distribution tile shows a histogram of all deal scores across your results. Each bar represents a score range (0-10, 11-20, and so on up to 91-100), and the height shows how many companies fall into that bucket. The shape of this histogram tells a story about the quality and consistency of your search.
- Right-skewed (peak on the right): Most companies scored high. This is the ideal shape — it means your query closely matched a strong market segment. You have a dense cluster of quality leads to work with.
- Left-skewed (peak on the left): Most companies scored low, with a long tail of a few higher performers. This typically happens when your query is too broad and pulls in tangentially related companies. The few high scorers may still be worth pursuing, but consider narrowing your search.
- Bell curve (peak in the middle): A normal distribution centered around 45-55 means you found a mixed set. There are leads worth pursuing at the top end and companies to skip at the bottom. Sort by score and focus on the upper third.
- Flat distribution (no clear peak): Scores are spread evenly across the range. This usually means your query captured a very diverse set of companies. The search was not bad, but the results need more manual filtering. Use the other tiles — especially categories and geographic spread — to identify clusters worth focusing on.
Over time, you will develop intuition for what a good histogram looks like for your specific market. A SaaS search in Berlin will have a different expected shape than a manufacturing search in the Ruhr Valley. Use the distribution as a feedback signal: each search teaches the histogram shape you should expect.
Tile 3: Aggregate Radar
The aggregate radar chart plots the average score across all six scoring dimensions — Digital Presence, Market Position, Growth Signals, Adoption Readiness, Content Quality, and Engagement Signals. Each axis runs from 0 at the center to 100 at the edge. The resulting shape reveals the collective strengths and weaknesses of your search results.
- Round and large: A well-balanced set of leads that score consistently across all dimensions. This is what you want — companies with strong digital presence, healthy growth signals, and good engagement. These leads are reliable and ready for outreach.
- Spiked in one direction: Your results are very strong on one dimension but weaker on others. For example, a spike on Digital Presence with a dip on Adoption Readiness could mean you found well-established companies that are satisfied with their current solutions. Useful to know before you craft your outreach angle — lead with a compelling reason to switch, not just a cold pitch.
- Small and round: Balanced but low-scoring. The companies are consistent but none stand out. This often happens in emerging markets or underserved geographies where businesses have limited digital footprints. The leads may still be good — they simply have less data available for scoring.
- Irregular and jagged: Your results are a mixed bag. Some companies are strong digitally but weak on growth, others have great engagement but low market position. When you see this shape, lean on the score distribution and top matches tiles to identify individual standouts rather than treating the set as a cohort.
The radar chart is especially powerful when you compare it across multiple searches. Run the same query for different cities or industries and compare the radar shapes side by side. The shape differences reveal how markets vary in maturity, digital adoption, and readiness for your offering.
Tiles 4 & 5: Categories and Geographic Spread
These two tiles work together. The categories tile shows the industry or business-type breakdown of your results, while the geographic spread tile maps where those companies are located. Combined, they answer two critical questions: did the search find the right type of companies, and are they concentrated or dispersed?
The category breakdown reveals how the scoring engine classified your results. If you searched for "marketing agencies in Amsterdam" and the categories show 60% Marketing Agencies, 20% Design Studios, and 20% PR Firms, that is useful signal. The 60% core is your target — the 20% design studios might be worth exploring if they offer marketing services, while the PR firms are probably noise you can filter out.
Categories also help you discover adjacent markets. If a significant portion of results fall into an unexpected category, it might indicate an opportunity you had not considered. A search for "HR software companies" that returns a cluster of payroll companies suggests an adjacent market worth investigating with a dedicated search.
Geographic concentration can be good or bad depending on your strategy. If you are planning local account-based outreach — say, visiting companies in a specific city — tight geographic clustering is exactly what you want. Seventy percent of results in one metro area means efficient territory coverage.
On the other hand, if you are mapping a national market and all results cluster in one region, you are missing significant portions of the addressable market. In that case, run separate searches for underrepresented regions to build a complete picture.
Use the geographic tile iteratively. After your initial search, identify the geographic gaps, run targeted follow-up searches for those areas, and build a comprehensive lead database that covers your entire target territory.
Tile 6: Email Coverage
The email coverage tile displays a donut chart splitting discovered emails into two categories: personal emails (name-based addresses like [email protected]) and generic emails (role-based addresses like [email protected] or [email protected]). This distinction matters enormously for outreach planning.
- 40%+ personal emails: You are in a strong position for direct outreach. Personal emails go straight to a decision-maker's inbox, bypassing gatekeepers and shared inboxes. A search that surfaces this level of personal email coverage means you can start outreach immediately without additional enrichment for most leads.
- 20-40% personal emails: A mixed result. You have direct contacts for some leads and will need enrichment or manual research for the rest. Prioritize the leads with personal emails for immediate outreach and use the Post-Search Wizard to enrich the remainder.
- Under 20% personal emails: Most of your leads only have generic contact information. This is common in industries where companies do not publicly list individual employee emails (manufacturing, construction, traditional services). Plan for a People Lookup step after your search to find the right contacts within these organizations.
- No emails found: Some results may have no discoverable email at all. This does not mean the lead is bad — it means the company has limited public contact information. Phone outreach or LinkedIn connection may be the better first-touch channel for these leads.
The email coverage tile directly informs your next step. High personal coverage means you can move to outreach faster. Low coverage means you should plan an enrichment step to find the right contacts before starting your campaign. Either way, knowing your coverage upfront prevents wasted effort.
Tiles 7 & 8: Top Matches and Performance
The final two tiles round out your analytics view. Top Matches highlights the highest-scoring leads from your search as quick-access cards, while the Performance tile provides timing statistics about the search itself — how long scanning, extraction, and scoring took.
The top matches tile surfaces your three to five highest-scoring leads prominently so you can jump straight to the most promising companies. This is convenient but comes with a caveat: the highest-scoring leads are starting points for investigation, not automatic winners.
A company might score 85+ because it has an excellent digital presence and strong growth signals, but that does not guarantee it is the right fit for your specific offering. Use the top matches to quickly open the deal score panel for each one, review the dimension breakdown, and make a human judgment call about fit.
Conversely, do not ignore companies scoring in the 60-70 range just because they did not make the top matches tile. A company with a slightly lower score but a perfect industry fit and an identified decision-maker email might be a better outreach target than a high-scoring company in a tangential market.
- Scan time: How long it took to discover companies matching your query. Longer scan times usually mean the system explored more sources to find results — a sign of thorough coverage rather than a problem.
- Extract time: How long it took to analyze each company's digital footprint and gather scoring data. Higher extract times correlate with deeper analysis — more assets examined means richer data for each lead.
- Score time: How long the AI scoring model took to evaluate all leads across six dimensions. This is typically the fastest phase and varies with result count.
The performance tile is most useful when comparing search depths. A Standard depth search will show shorter times than a Deep search, but the Deep search typically produces higher-quality scores because it examines more digital assets per company. If your scores feel thin or unreliable, consider running the same query at a deeper level to see if the additional analysis changes the picture.
Putting It All Together
The real power of the analytics sidebar emerges when you read the tiles as a connected story rather than eight independent charts. Here is a practical workflow that experienced LeadScoutr users follow after every search:
Check Quick Stats
Glance at total results, average score, and high-scorer count. If the numbers look weak (under 20 results or under 45 average score), refine your query and run again before reviewing anything else.
Read the radar shape
A round, large radar means a well-balanced set of leads. Spikes or dips reveal the collective personality of your results — strong digital presence but weak adoption readiness suggests established companies that may be hard to convert without a compelling trigger.
Examine score distribution
A right-skewed histogram confirms quality. A flat or left-skewed shape means you need to cherry-pick the best leads manually rather than working the list top to bottom.
Review categories
Confirm that the majority of results fall into your target category. Note any unexpected clusters — they might represent adjacent markets worth a dedicated follow-up search.
Check geographic spread
Verify coverage across your target territory. If results cluster in one area, plan supplemental searches for underrepresented regions.
Assess email coverage
If personal email coverage is above 40%, you can move to outreach planning quickly. Below that threshold, budget for a People Lookup step to find decision-maker contacts.
Start with top matches
Open the deal score panel for your highest scorers. Review their dimension breakdowns and AI-generated summaries. Make a human call on which ones deserve immediate attention.
Launch the Post-Search Wizard
Use the 5-step wizard to shortlist your best leads, organize them into a CRM list, enrich company data, find people at priority accounts, and export your final set. The wizard turns analytics insight into actionable pipeline.
This workflow takes about two minutes per search. Over time, it becomes second nature — you will instinctively know what a healthy search looks like for your market and immediately spot when something is off. The analytics sidebar is not extra chrome on top of your results; it is the control panel that makes every search more intentional and every outreach campaign more effective.
Each search you run adds to your pattern library. After ten or twenty searches, you will know that a SaaS query in the Nordics typically produces a right-skewed distribution with strong digital presence, or that a manufacturing query in Southern Germany yields lower email coverage but higher market position scores. This accumulated knowledge compounds — and it starts with reading the eight tiles instead of skipping past them.
Ready to read your own analytics?
LeadScoutr's AI Search generates the full 8-tile analytics sidebar with every search. Combine it with Deal Scoring for per-lead dimension breakdowns, and use the Post-Search Wizard to turn insights into pipeline.