Add Maple
IIEX North America

Voted #1 by industry experts and live audience

AI Launchpad Winner

AddMaple capabilities

A modern, connected workflow for quant and qual research.

A platform for faster AND broader research. Get ranked statistical relationships across ALL variables, quant AND qual.

Find key drivers and clusters across mixed data. Spot new evidence and share it sooner than previously imagined.

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Connect raw surveys, trackers, concept tests, open ends, transcripts

AddMaple workspace connecting quant and qual research data with statistical analysis
Andrea Knight Dolan

“AddMaple creates instant chart dashboards that let you analyze your survey data visually and is one of the best ways I've found to conduct AI-powered thematic analysis of open-ended results.”

Andrea Knight Dolan, Professor at University of Toronto, ex-Google
Susan Baier

“We have shaved a full month off our project timeline in terms of analysis and visualization of our data.”

Susan Baier, Founder & CEO, Audience Audit
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Explore AddMaple's Capabilities

Choose the view closest to how your team works, or browse every public capability across preparation, discovery, and delivery.

For in-house insights teams

See how teams analyze trackers, surveys, and segmentation studies, answer follow-up questions, and help stakeholders use evidence long after the research is concluded.

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For research agencies

See how teams streamline quant and qual project delivery, deliver more comprehensive insights to clients, and share them through explorable deliverables and branded decks.

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Browse supported inputs, methods, and integrations across preparation, analysis, and delivery.

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Analytics services

Analytics support when you need it.

Work with AddMaple's research analysts on a current study, from data preparation and advanced analysis to stakeholder-ready delivery.

  • Data preparation and weighted crosstabs
  • Segmentation, clustering, and advanced analysis
  • Dashboards, Insight Hubs, and branded decks
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Today

Research workflows often split preparation, analysis, coding, statistics, and delivery across separate tools.

With AddMaple

One inspectable workflow connects preparation, discovery, quant and qual analysis, and stakeholder delivery.

The workflow

One connected workflow

Move from the data you have to evidence people can use — without handing the project off between disconnected tools.

Prepare → Discover → Deliver

Discover

Find what matters, what is connected, and how strong the evidence is.

AddMaple summary view showing distributions across every variable on import

See every variable as soon as the file lands

Charts and distributions across the whole study first — then choose where to investigate further.

AddMaple banner table with segment columns, count and percent cells, and blue/pink significance shading

Stop scanning dense grids

Rank what differs, inspect significance, and export the Excel tab books researchers actually deliver.

AddMaple related columns list with ranked relationships, stats panel, and stacked bar chart with segment legend

Thousands of tests without running them yourself

Pick a column and AddMaple ranks the statistically strongest relationships across the rest of the project.

AddMaple key driver analysis ranking factors by relative influence with outcome accuracy and tier labels

What is most connected to the outcome

Rank the factors that matter, then inspect the model before it becomes a recommendation.

AddMaple linear regression with coefficient, confidence interval, R², fitted scatter plot, and interpretation

What is the estimated relationship?

Linear and logistic regression with fitted charts, Elastic Net multivariate drivers, and PCA — inspectable coefficients and structure in the same project.

AddMaple Create Clusters flow showing algorithm choice and cluster settings

Which groups actually exist in this audience?

Compare clustering approaches suited to mixed survey data, then profile the groups you can use.

AddMaple mental availability view comparing brand reach across buying situations

Which brands come to mind in which buying situations?

Compare Category Entry Point strengths, weaknesses, and whitespace in the same project as the rest of the study.

AddMaple qualitative themes linked to quantitative crosstab evidence

Turn what people say into evidence you can test

Coded themes become project variables you can banner, test, and use in drivers — while remaining linked to the original words.

AddMaple Ask Maple analysis view with a project question and an evidence summary

AI operates the analysis. It does not invent it.

Ask a question. Maple runs the appropriate AddMaple table, test, or model. You inspect the actual output.

Built for research you have to defend

Inspect the path from source to shared finding.

Source integrity, statistical transparency, and controlled sharing keep the workflow reviewable as it moves from analysis to delivery.

Source integrity & auditability

Non-destructive transformations and traceable methods keep the underlying research defensible.

Statistical testing & significance

Which differences are evidence, not noise? Named tests, effect sizes, and multiple-comparison correction — selected by variable type, with inspectable results.

Controlled sharing

Share explorable evidence with controlled access — password-protected Hubs and governed read-only views for stakeholders.

What teams get

Keep the evidence useful after the first answer.

agency

For agencies

Deliver stronger client stories, answer follow-up questions without restarting the analysis, and keep clients engaged through explorable deliverables.

in-house

For in-house teams

Answer the next question without restarting the analysis — and keep evidence usable across stakeholders and studies.

Supported inputs and methods

The detail behind the workflow.

File formats, integrations, methods, and output options supported across AddMaple.

Data Prep, Trackers & Import

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Survey and research data sources

Import fieldwork from Qualtrics, Decipher, Alchemer, and QuestionPro — plus SPSS .sav, Excel, CSV, JSON, Typeform, SurveyMonkey, Tally, and Google Drive. Pick files from SharePoint or connect governed enterprise sources without a separate processing handoff.

SharePoint & enterprise data connections

Import CSV, Excel, and SPSS from SharePoint in your Microsoft 365 tenant, or connect AWS Athena and other governed enterprise sources so teams can create projects from SQL queries and shared file stores.

Schema & question-key import

Upload question keys and data dictionaries to map technical column names to full question text, labels, and grouped batteries on import.

Survey-native structures

Handle multi-selects, grids, Likert and opinion scales, grouped variables, tags, and survey metadata as research data.

Survey metrics, scores & scales

Build NPS, CSAT, CES, UMUX, Likert top-box and net scores, composite indices, and reliability measures such as Cronbach's alpha in the same project as the analysis.

Weighted analysis

Apply survey weights to tables, banners, and analysis so results reflect the intended population without exporting to a separate weighting tool.

Tracker trends & wave comparison

Compare waves, track movement in key metrics over time, and analyse longitudinal tracker data in the same project as cross-sectional cuts.

Python & R programmatic access

You are not trapped when AddMaple does not have a specialist method — connect Python or R notebooks, run your own analysis, and write columns back to the same governed project.

Statistics, Drivers & Segmentation

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Data Table Studio

Build interactive banner tables and ranked crosstabs in-product — significance shading, bases and indices, subgroup ranking by statistical strength, crosstab-level AI, and formatted Excel tab books with layouts and brand colors.

Statistical testing

Use named tests, effect sizes, multiple-comparison correction, and inspectable significance outputs.

Relationship discovery

Pick any column and AddMaple automatically runs chi-square, ANOVA, t-tests, Kruskal-Wallis, and correlation against every other variable — ranking thousands of pairwise results by significance and effect size without manual test selection.

Key driver analysis

Rank the factors that matter most using target-appropriate methods including Random Forest and regularised models, with directional evidence where appropriate.

Regression, PCA & multivariate modelling

Linear and logistic regression with fitted charts and coefficients, Elastic Net multivariate key-driver models, and PCA with optional Varimax rotation — in the same project as tables and banners.

PCA & dimension reduction

Explore latent structure in correlated attitude and rating batteries with principal component analysis, loadings, variance explained, and optional Varimax rotation.

Segmentation and clustering

Compare clustering approaches suited to numeric, categorical, or mixed survey data, then review quality before profiling the groups.

Segment profiling & comparison

Profile who each segment is, what differentiates them, and compare lift vs overall for banners, charts, and presentations.

MaxDiff, TURF & Conjoint

Run specialist preference and portfolio methods for item importance, reach, optimal combinations, and attribute trade-offs in the same project as the rest of the study.

Mental Availability & CEP analysis

Compare which brands come to mind across buying situations and identify Category Entry Point strengths, weaknesses, and whitespace opportunities.

AI & Text Analysis

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Topic-based sentiment on open text

See which themes drive positive, neutral, or negative feedback — not just overall tone — with AI coding that keeps verbatims inspectable.

Quant and qual together

Connect coded themes to survey variables, cuts, charts, and statistical evidence in the same project.

Ask Maple

Ask questions in project context and let Maple operate AddMaple analysis while the underlying outputs remain inspectable.

Use AddMaple where you work

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Team questions in the tools you use

Let teammates ask follow-up questions about a live project in Slack, Cursor, Claude, ChatGPT, and other existing tools with governed access to AddMaple analysis.

Slack team analysis

Analyze team projects in Slack channels, threads, and DMs with the same toolkit as Ask Maple. Microsoft Teams coming soon.

MCP agent access

The AddMaple analysis engine can be operated from Cursor, Claude, ChatGPT, and other MCP hosts — summaries, crosstabs, drivers, segmentation, and text analysis with the same permissions as the browser.

Typeform live connector

Sign in to Typeform, choose a form, and analyze responses in AddMaple — responses sync when you open the project without manual CSV exports.

SurveyMonkey connector

Connect SurveyMonkey, pick a survey, and start analyzing in AddMaple without downloading and re-uploading export files.

Tally forms connector

Paste a Tally API key, select a form, and analyze submissions in the same governed project as the rest of your research workflow.

Google Drive import

Pick CSV, Excel, or SPSS files from Google Drive and import them straight into a new AddMaple project.

Product API keys & automation

Mint bearer tokens for Python, R, MCP hosts, and dataset API access — connect notebooks and automation to the same team projects analysts use in the app.

Embed & share chart links

Share chart links in Slack and email, or embed approved outputs in Notion, websites, and stakeholder tools without rebuilding slides.

Enterprise data connections

Connect governed sources such as SharePoint, AWS Athena, and secure data lakes so teams can import files or create projects from SQL queries without manual handoffs between systems.

Visualization & Exploration

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Chart dashboard on import

See every variable summarized as charts and distributions the moment a file lands — expand, filter, and pivot from the dashboard without building a report first.

Pivot charts & cross-column views

Compare any columns side by side from the sentence builder — stacked bars, grouped cuts, percentage types, and instant stats on the pivot you are viewing.

Likert & opinion scale charts

Chart batteries of agreement, satisfaction, and rating scales with layouts built for survey research — including grouped Likert and neutral-aligned views.

Filters, segments & subgroup views

Apply global AND/OR filters, save reusable audience definitions, and build subgroup views that update every chart, table, and statistical test in the project.

Time series & tracker trend charts

Plot movement over dates, waves, or ordered categories with line and column trend views suited to trackers and recurring fieldwork.

Geographic maps

Map categorical and numeric results by region or country when your dataset includes geographic columns — explore spatial patterns without a separate mapping tool.

Scatter, box plot & numeric charts

Inspect relationships and distributions with scatter plots, box plots, mean dot plots, bubble charts, and histogram-style views for numeric survey fields.

AI chart explanations

Click Explain Chart on any pivot for an AI summary of what the current view shows — inspectable alongside the underlying numbers, not a replacement for them.

Row-by-row respondent view

Read individual records in full context, navigate cohorts row by row, and validate patterns against verbatims before you present a cut.

Table, pivot & chart views

Switch between chart dashboard, pivot tables, row-by-row records, and Data Table Studio without rebuilding your filters or audience definition.

Sharing, Privacy & Outputs

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Charts and editable exports

Move selected findings into editable PowerPoint charts and presentation-ready outputs — alongside Data Table Studio for Excel tab books and formatted crosstab workbooks.

Story Dashboards & Insight Hubs

Save findings to Insights and Collections, build page-based Story Dashboards, then publish controlled explorable Hubs where stakeholders filter data and ask follow-up questions.

Client self-serve exploration in Hubs

Let clients slice explorable published Hubs on their own — governed column access, filters, and plain-English AI questions without reopening the full analyst project.

Controlled sharing

Share explorable evidence with governed access, including password-protected Hubs and read-only stakeholder views.

Bring one real research workflow.

See how AddMaple would prepare the data, surface the strongest evidence, and turn the result into something clients or stakeholders can keep exploring.

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