Market research dashboard: segments, demand, and evidence

A market research dashboard compares survey answers and sales trends across defined customer segments. Its useful output is a clear account of where stated interest and actual purchasing agree, where they differ, and how much evidence supports each finding.

Start with a question the supplied files can answer

Suppose an Ohio business supplies packaging to other companies. Its commercial team wants to know whether interest in a consolidated delivery option differs between midmarket and enterprise accounts, and whether those segments are growing.

That question can be answered from a survey export and a sales export. The files cannot establish total US demand or explain why a particular buyer purchased. Keep those limits in the heading and review notes rather than letting an attractive percentage imply a broader conclusion.

Choose the measures before arranging the display. The companion guide to market research KPIs covers measure selection; this page concentrates on assembling a review from the evidence already available.

Prepare the files at their own level of detail

Use one row per account response for the research table, with response ID, account ID, segment, question version, fieldwork date, and answer. If several people represent one account, decide whether the measure describes people or accounts before removing duplicates. Do not silently count both ways.

Use one row per invoice line for sales, with invoice ID, account ID, segment, reporting period, and net sales in USD. Assign segments using a documented rule, such as the account classification at the start of the comparison. Otherwise an account changing groups can create apparent growth in one segment and decline in another.

Retain the exact question wording across comparable waves. Pew Research Center's guidance on survey questions explains that wording and question context matter when measuring change over time. A change in wording belongs in the evidence note, even when the segment labels stay the same.

Work the response counts before calculating percentages

Here is the complete illustrative response file, collected September 14 through September 18, 2026. Every record is a completed questionnaire, but one account skipped the delivery question. The blank below is an empty spreadsheet cell, not the word "blank."

Place that table in columns A:D of a worksheet named Responses, starting with headers in row 1. In a summary sheet, put the segment name in A2. These Excel formulas return questionnaires in B2, valid answers in C2, favorable answers in D2, and favorable share in E2:

=COUNTIFS(Responses!$C$2:$C$9,A2)
=COUNTIFS(Responses!$C$2:$C$9,A2,Responses!$D$2:$D$9,"Yes")+COUNTIFS(Responses!$C$2:$C$9,A2,Responses!$D$2:$D$9,"No")
=COUNTIFS(Responses!$C$2:$C$9,A2,Responses!$D$2:$D$9,"Yes")
=IF(C2=0,"",D2/C2)

Microsoft documents COUNTIFS as counting records where all specified criteria match. The explicit Yes and No counts also prevent other response codes from entering the valid-answer base accidentally. Covirage is not affiliated with Microsoft.

Percentages are rounded to one decimal place after division. The total is 3 / 7, not the average of the displayed segment percentages. Reconcile the eight response IDs to the imported export, then reconcile seven valid answers plus one missing answer to those eight records.

These small counts demonstrate the method. They are a reason to investigate a segment, not a reliable basis for declaring a market preference.

Add comparable sales without multiplying the rows

Summarize sales by segment independently. Do not attach every invoice to every response from the same segment: that would repeat sales for each respondent.

The sales export below is already totaled by segment for July 1 through September 30 in 2025 and 2026. It includes all customers in each segment, not just the respondents. Net sales include the applicable credits and returns.

Put this table's inputs in A:C of a separate SalesSummary sheet. Calculate change in D2 and growth in E2:

=C2-B2
=IF(B2=0,"",D2/B2)

Fill down for both segments. On the total row, use =SUM(C2:C3)-SUM(B2:B3) for the dollar change and =D4/SUM(B2:B3) for growth. The check is 280,000 + 30,000 = 310,000. Overall growth is 30,000 / 280,000 = 10.7%, rounded to one decimal place.

Keep sales growth beside the survey share, with separate labels. Midmarket has higher stated interest and faster sales growth in this illustration. The dashboard has not shown that interest caused the growth. Nor is segment sales growth market share, which needs a market-wide denominator.

Arrange the review around evidence and a next step

Use a segment table with favorable share, valid-answer count, sales growth, research dates, and a short limitation. Show a sales trend separately if several periods are available; a single comparison should not masquerade as a long trend.

The research owner confirms question comparability and respondent coverage. Sales operations confirms the segment mapping and sales totals. The commercial manager decides whether the finding merits customer interviews, a pricing discussion, or a better designed research wave. Record that action beside its supporting rows.

If the question is which products customers buy together, use market basket analysis instead. That is a transaction question with a different unit of evidence.

Where it goes wrong

• Skipped answers counted as No. This changes the question denominator and understates the favorable share.
• Respondents treated as the whole market. Customer feedback needs a coverage statement; a dashboard does not fix selection bias.
• Periods or segment rules change. Compare matching periods and disclose account migrations before interpreting growth.
• Sales repeat after a join. Reconcile each source independently before placing its segment totals together.
• Interest presented as causation. A survey and sales can move together without proving what caused purchases.

Do this on your own file in Covirage

Bring your survey response file and sales export with segment definitions and reporting dates. Covirage maps the columns; its tools compute and check the figures, and the external AI model explains the results with every figure traced to its rows. Create a free Covirage account and bring a sample of your own data; creating the account takes about a minute.

See sales insights for commercial teams for the supporting business context.