Mintel vs Tastewise: Features, Data and Pricing Compared (2026)

Two platforms, both sold to the same insights director, and almost no overlap in how they collect information.

Mintel sends people into stores to open packets and log what is inside. Tastewise reads what 4 million restaurants put on their menus.

One produces a written report. The other produces a sell-in story.

Anyone comparing Mintel vs Tastewise usually starts with the wrong question. It is not about which platform holds better data.

The real question: what does your team do the morning after the data arrives?

I have gone through both platforms, both pricing models and every coverage claim each one publishes. Below is the feature-level breakdown, the real cost of each, and an honest read on where both fall short.

Mintel vs Tastewise: quick comparison

One line ends the debate for a lot of buyers. If beauty, pet care or household sits anywhere in your portfolio, Tastewise holds no data for you.

What is Mintel?

Mintel is a market intelligence provider founded in London in 1972 by Nicholas Berry. It runs around 1,600 staff and 300+ analysts across 13 offices, including London, Chicago, Shanghai, Belfast and Kuala Lumpur.

Matthew Nelson runs the business as Global CEO, with Peter Haigh as Executive Chairman.

Clients include PepsiCo, Nestlé, Mars, Kraft Heinz, Campbell's and Kroger.

The core product is understanding. Mintel tells you how a category behaves, what competitors launched, and what consumers say they want.

Mintel platform and products

Mintel sells through two doors.

You buy individual reports from the store. Or you subscribe to On-Demand and get platform access to the databases.

Mintel GNPD

The Global New Products Database is the piece with no real rival. GNPD tracks 40,000 new product launches every month across 86 markets and 46 categories.

Coverage spans food, drink, beauty, personal care, pet, health and hygiene.

A field team does the work by hand. They buy the product, open it, and log ingredients, packaging format, pack size and every claim printed on the front.

I think manual collection is the part buyers undervalue. Scraping gets you volume.

It does not give you a consistent read on whether a pack says "high protein" or "source of protein". Not across 86 markets and eight years of history.

GNPD now sits inside Leap, so you ask innovation questions in plain language rather than building filters. The Plan-IT tool handles market growth analysis, and email alerts fire when a competitor launches in your category.

Mintel Leap

Leap is the AI layer. It answers questions using Mintel's own research and analyst work, and nothing else.

Because it never queries the open web, it avoids the invented-citation problem that hits general chatbots on research questions. Every answer links back to the reports behind it.

That closed loop is a real design choice with a real trade-off. You get traceable answers. You also get nothing outside what Mintel already published.

Mintel Spark and Landscapes

Spark generates and tests early-stage product concepts. Mintel launched it in 2024 for teams working on front-end innovation.

Landscapes handles attribute forecasting. It shows which flavours, ingredients, formats and claims are growing now, and which ones look set to grow next.

Global Consumer, Market Dynamics and Macro Trends

Global Consumer gives survey data across 36 markets that generate 85% of world GDP. Same instrument in every market, so a brand can compare attitudes in Japan against Brazil without adjusting for methodology.

Market Dynamics connects market sizing to consumer sentiment and brand activity.

Macro Trends runs 300 monthly observations that ladder up into 7 trend drivers. Purchase Intelligence sits alongside these in the On-Demand bundle.

Mintel also added a partnership with Dragonfly AI in 2026, bringing predictive attention analytics into the mix.

Who Mintel suits

Insights teams, strategy teams and R&D groups inside multi-category consumer goods companies. Anyone whose planning window runs in years rather than weeks.

It also suits teams that already employ analysts. The value shows up when someone internal can interpret the research and turn it into a recommendation.

Mintel pros and cons

What is Tastewise?

Tastewise is an AI intelligence platform built for food and beverage.

Alon Chen and Eyal Gaon founded it in 2017. Chen previously ran marketing for Google across Israel and Greece. Gaon serves as CTO.

The company raised a $50 million Series B in June 2025, led by TELUS Global Ventures with Duo Partners, Peakbridge, Disruptive AI and PICO. Total funding now sits past $70 million.

Customers include PepsiCo, Nestlé, Mars, Kraft Heinz, Campbell's and Givaudan. Headcount runs around 100 to 140, with the company now listing New York as its base.

The core product is action. Tastewise validates a signal, then produces the asset your team needs for the meeting.

Tastewise platform and AI agents

The data sits underneath. Agents sit on top and do the work.

TasteGPT and the agent library

TasteGPT is the conversational front end. It claims 96% accuracy on food questions, built on more than seven years of food-specific taxonomies.

Thirteen prebuilt agents handle defined jobs. The list covers trends, competitor tracking, whitespace, concepts, recipes, formulation, insights, raw data pulls, sales and marketing.

The Sales Agent is the one that separates Tastewise from a research subscription. It builds an operator-specific sell-in narrative from live menu data and demand evidence.

A rep walks into the buyer meeting with a story rather than a chart.

Agent Builder and custom agents

Teams that want a workflow nobody sells off the shelf can build one without code. Tastewise puts custom agents at two to four weeks from intake to production.

Flavor Forecast

Flavor Forecast predicts trend lifecycle. It tries to call which flavours and ingredients move from emerging to mainstream, and when.

Sales and marketing solutions

Tastewise packages the platform into named solutions rather than raw modules.

Retail Sales Enablement, Foodservice Sales Enablement, Product Innovation and Renovation, Consumer Marketing, Audience Discovery and Matching, Consumer Insights and Retail Intelligence.

Retail Sales Enablement covers category management narratives and shelf planning. Foodservice Sales Enablement targets operator meetings and menu placement.

The company claims clients cut launch timelines by 6 to 8 months. Treat that as a vendor figure until your own pilot confirms it.

Who Tastewise suits

Food and beverage teams working against a deadline. Category managers preparing a line review, marketers scoping a campaign, R&D leads validating a concept before development spend.

It suits teams without a large internal insights function, because the agent does the interpretation an analyst would otherwise handle.

Tastewise pros and cons

Mintel vs Tastewise: data coverage compared

This is where the two platforms stop being alternatives and start being different products.

What Mintel measures

Stated intent and shipped product.

A survey records what a person says about sugar reduction. GNPD records what a manufacturer put on shelf, with the claim, the format and the ingredient deck.

Both hold structure. Both compare cleanly across markets and years.

What Tastewise measures

Observed behaviour. What a chef put on the menu, what someone bought online, what a home cook searched for, what people posted about.

Here is one output rather than a claim. Tastewise US foodservice data put the average July 2026 menu item price at $9.14 in quick service and $25.26 in fine dining.

Fast casual sat at $12.26, midscale at $13.39, casual dining at $15.78. Quick service climbed 6.9% over the year.

No survey produces those numbers. They come from reading menus at scale.

Why the two datasets disagree

Stated intent and purchase behaviour drift apart, and the gap is often the interesting part.

A survey might show strong interest in low sugar drinks while menu data shows the category flat in casual dining.

Neither reading is wrong. They measure different things, and a team treating them as the same thing will misread both.

(This is the strongest argument for running both, and it is a better argument than either vendor makes on its own site.)

Mintel vs Tastewise: AI features compared

Both ship AI. They point it at different halves of the job.

Closed-loop answers vs agent output

Leap gives you a sourced answer to a research question. Tastewise agents give you a draft you edit.

Teams with strong internal insights people get more from Leap, because interpretation is the value they add. Teams without that function get more from the agents.

One honest caveat. An agent-written sell-in story still needs a senior review before a buyer meeting.

I have watched teams skip that step and walk into a line review with a number nobody could defend.

One more piece deserves weight here, and it sits low on the Tastewise site: the Model Context Protocol. Tastewise runs an MCP gateway, so its data answers questions asked from Claude, ChatGPT, Copilot or Perplexity. Mintel has nothing equivalent in public.

How the Black Swan acquisition changed the gap

In June 2025, Mintel acquired Black Swan Data.

Black Swan is a London company founded in 2011 by Steve King and Hugo Amos. It reads unprompted consumer conversation on TikTok and Instagram to predict emerging demand, and it already worked with PepsiCo and Nestlé.

Read that again. Mintel bought the exact capability Tastewise sells as its edge.

Comparison pages written before mid-2025 frame this as slow analysts against fast AI. That framing is out of date. The real gap now sits in foodservice depth, not in whether Mintel can read social data.

How far the gap closes depends on how well the two datasets get stitched together, and that work is still in progress.

Integrations and workflow fit

Mintel integrates as a data source. Tastewise integrates as a working layer inside the tools your commercial team already opens.

That difference matters more than the row count. A category manager will not log into a research portal before a Tuesday call.

They will read a Slack message.

Mintel vs Tastewise pricing

Pricing is the section both vendors make hardest to research, so here is what each one publishes and what it works out to.

Mintel pricing

Individual US market intelligence reports list at $4,995 each. Bundle savings run 10% for two, 15% for three and 20% for four or more.

Reports arrive as a PDF, a PowerPoint and an Excel databook, plus an interactive version on the platform. You can pay by credit card or purchase order.

The Mintel pricing page covers the On-Demand subscription, which bundles GNPD, Global Consumer, Market Dynamics, Macro Trends, Landscapes, Purchase Intelligence, Leap and Spark. Mintel publishes no figure for it.

A free Spotlight tier gives you articles, newsletters and podcasts. It does not open the platform or the full reports.

Tastewise pricing

The Tastewise pricing page runs a calculator and a proposal request. Plans scale with modules and market coverage, and an enterprise tier exists for multi-brand portfolios with role-based permissions.

No public number appears anywhere on tastewise.io.

One does appear on its cloud marketplace listing: an Entry package at $5,000 per month, charged per user, on a one-month contract. A twelve-month term cuts up to 17%, and the listing states a no-refund policy.

Read the terms and one thing stands out. Cost scales with headcount, and headcount is the only variable. No feature tiers, no usage add-ons.

Total cost if you run both

Do the arithmetic before the discovery call.

Four Mintel reports at the 20% bundle rate land near $16,000 as a one-time spend. A three-seat Tastewise Entry package at list works out to $15,000 a month, or $180,000 a year before negotiation.

Those are different shapes of commitment. One is a purchase. The other grows every time a fourth person asks for a login.

What to do: Lock your seat count before the first call. Per-user pricing punishes teams that hand out access freely.

Mintel vs Tastewise: which one should you choose

Four routes, depending on team shape and timeline.

1. Choose Mintel if

• Your portfolio runs past food and drink into beauty, pet care or household
• You need launch tracking across dozens of markets with consistent categorisation
• You have analysts internally who turn research into recommendations
• Your planning window runs in years
• You would rather buy four reports than sign a per-seat subscription

2. Choose Tastewise if

• Food and beverage is your only category
• You need menu-level and operator-level detail no survey captures
• Your team wants a drafted sell-in story rather than a chapter to read
• You have no internal insights function to interpret raw research
• You want the data queryable from the AI tools your team already uses

3. Run both if

• You want to spot demand in Tastewise and check competitive whitespace in GNPD
• Your insights team and your commercial team ask different questions
• You sell into both grocery and foodservice channels
• Budget allows a research subscription alongside an activation platform

4. Look elsewhere if

Neither one fits every brief.

Circana, formed from the IRI and NPD merger, owns retail scanner and panel data if your question is what sold rather than what launched. NIQ covers similar ground.

Euromonitor Passport and Kantar compete with Mintel on breadth. Innova Market Insights runs closest to GNPD on launch tracking, and Datassential goes deeper on US foodservice operators.

Tastewise itself publishes comparison pages against Circana and Innova, which tells you where it sees the real fight.

Where both platforms stop

Both tools answer what to build and where demand is heading. Then the job changes shape completely.

Retail is the tidier side. Grocery chains run category managers with published review cycles, and distributors like UNFI and KeHE run catalogs and onboarding processes. The path is competitive but legible.

Foodservice is messier. You are chasing purchasing managers at hotel groups and food and beverage directors at institutional operators.

Add executive chefs at chains, buyers at Sysco or US Foods, and a broker network on top.

A single listing decision can touch six people across three companies. Mapping that buying group is not a research question. It is a contact data question.

Say the Trends Agent flags a functional ingredient surging in Western US quick service menus. Good.

Now find the person at that chain who approves menu changes, and reach them before the incumbent supplier does. Neither platform holds that record. They were never built to.

Mintel vs Tastewise vs SMARTe

SMARTe sits in a different category. It covers the execution half of the problem the other two leave open.

What SMARTe adds

SMARTe holds 289M+ verified B2B contacts and 66M+ company profiles across 200+ countries.

US mobile and direct dial coverage runs above 75%, and global direct dial coverage sits above 50% across EMEA, APAC and LATAM. Email reach hits 86% of verified US decision-makers.

CRM enrichment matches at 90% or better. That matters because data decay turns last year's line review contact list into dead weight.

Direct dials carry more weight in this market than in software sales. A category manager screens inbound email far harder than a VP of engineering does.

A verified mobile number is often the only route that works.

Native Bombora intent data flags which accounts research a category right now. Pair that with leadership changes or new store openings and you get timing, not just names.

SMARTe is enterprise only, from $15,000 a year, with credits starting at $0.30 and no per-seat fees. There is no free or self-serve tier, so evaluation runs through a sample match against your own target accounts.

Where SMARTe does not fit

SMARTe holds no consumer data, no menu data and no shelf data. It will not tell you which flavour to launch or which claim is winning.

Its customer base also sits mainly in technology and services, not consumer goods. A CPG team should treat it as a data layer, not a category expert.

It is also a sizeable commitment next to a single Mintel report. At $15,000 a year it suits teams running a real, continuous sell-in motion, not a one-off project.

If the question is what consumers want, buy Mintel or Tastewise. SMARTe answers the question that comes after.

Teams running this properly treat it as two line items, not competing ones. Consumer intelligence sets the strategy, and a B2B contact database runs the sell-in motion.

Book a demo and ask for a sample match to see verified mobile numbers inside your own target retail and foodservice accounts.

The part the vendor pages leave out

Research budgets and sales budgets sit in different places, which is why this gap goes unnoticed for so long.

The insights team buys Mintel or Tastewise, proves a demand signal, and hands a deck to commercial. Commercial then spends three weeks working out who to send it to.

Good intelligence loses value on a clock. A trend spotted seven months early is worth nothing if the meeting lands after the shelf reset.

The teams that win the listing are rarely the ones with the best research. They are the ones who got in front of the buyer while the research still mattered.