Tina Louise Thompson works with consumer and social-listening insights to help food and consumer-goods brands find growth opportunities, including ideas for retail and category marketing. Thompson's posts describe Sweet Spot as a team of specialists that helps grow CPG brands.
4.6K followersAI shoppingBased on 14 posts · latest Sep 2026
Tina Louise Thompson is most useful for turning consumer and social-listening insights into practical food and CPG retail or campaign ideas.
Best for
Food or beverage brands wanting to turn existing social conversation into retail activation without a new product launch.
Not for
Brands seeking large consumer reach, guaranteed impressions, standard rate cards, or meat-replacement positioning.
Key takeaways
Social listening should reveal existing consumer demand, not just count mentions.
Grocery shelves can turn social colour trends into cross-category displays.
Plant-based growth is shifting from meat imitation to food layering.
Check first: Confirm available formats, pricing, audience demographics, performance data, and whether they offer sponsorship packages.
Main ideas
Social listening should reveal existing consumer demand, not just count mentions · Grocery shelves should turn social colour trends into cross-category displays · Plant-based growth is shifting from meat imitation to food layering
Tina Louise Thompson works with consumer and social-listening insights, especially for food and consumer-goods brands.
Their LinkedIn posts show how they turn consumer behaviour and category data into practical ideas: for example, using shoppers’ existing Vaseline hacks to frame a campaign, or turning a colour-led gifting trend into a cross-category grocery display.
They also write about changing food preferences, ageing consumers and AI-assisted shopping.
Thompson’s distinctive strength is connecting observed behaviour to decisions brands and retailers can act on.
In the Vaseline example, they outline the steps from listening to campaign: test consumer-created hacks, validate useful ones, reject unsafe ones, then build a platform around them.
In the Picnic Sunshine Basket post, they turn a social trend into a specific retail proposal: a yellow-led fixture, cross-category products and several seasonal occasions, using existing products rather than requiring new ones.
Their plant-based analysis shows another side of the approach: separate growth in familiar ingredients from declines in meat substitutes, then reframe the need around adding ingredients to meals people already enjoy.
A useful counterpoint is their writing on AI: alongside the idea of an “AI shelf,” they argue that people must check AI outputs and that entry-level work helps people develop judgement.
Follow Thompson for examples of how consumer signals can change a marketing or retail decision, alongside their views on the limits of AI.
Tina Louise Thompson's recurring argument is that brands should act on consumer behaviour already visible in public conversation and on the shelf.
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They treat social listening as unpaid consumer R&D, use large datasets to challenge marketing assumptions, and translate trends into retail and product decisions.
Their priorities include validating before amplification, cross-category merchandising, food layering rather than meat replacement, making product information legible to AI shopping tools, and preserving human judgement in AI-assisted work.
They also favour a joined-up specialist network over a big agency model for CPG growth.
Social listening should reveal existing consumer demand, not just count mentions
Thompson argues that public posts reveal how consumers already use a product—and amount to unpaid consumer R&D.
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The commercial value comes from validation: test shared behaviours, confirm which are useful, debunk unsafe or unsuitable ones, then build the strongest into a brand platform. They say most businesses are not structured to hear this commercially, leaving the insight unvalidated and unclaimed.
Vaseline: more than 3.5 million posts showed people using the product for perfume tricks, leather shine and everyday fixes.
Thompson reports the campaign generated 63.3 million interactions, 13.9% retail sales value growth and 43% e-commerce growth within a month.
Vaseline Verified validated the helpful hacks and debunked the rest.
Grocery shelves should turn social colour trends into cross-category displays
Thompson argues that colour blocking is well established in beauty and wellness but underused in grocery, where shoppers respond to bright, coordinated gift edits online.
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They say colour can guide shoppers in-store, signalling gifting, mood and occasion without explanation. Cross-category displays of snacks, drinks and small gifts encourage shoppers to build baskets rather than browse single items.
The Picnic Sunshine Basket is a yellow-led fixture bundling lemon drinks, sweet treats, candles, mugs, napkins and self-care items.
Thompson says one colour concept can stretch across teacher gifting, get-well-soon, park picnics and summer hosting, using better storytelling with existing products rather than new product development.
The post cites a 2026 consumer trends report built from 62 million data points across social and search.
Plant-based growth is shifting from meat imitation to food layering
Thompson argues that plant-based is not dying but losing the disguise.
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Consumers are moving away from products designed to imitate meat and toward familiar ingredients such as beans, pulses, tofu and tempeh. They propose food layering: adding protein and fibre to meals people already enjoy, rather than asking them to replace meat.
UK unit sales in the first half of 2026: beans, pulses, tofu and tempeh rose 7.3%, while plant-based meat alternatives fell 4.3%.
Tempeh sales rose 71.5%; dried beans, peas and lentils rose 16.7%; premium canned and jarred butter beans grew more than 30%.
Thompson suggests smoky tempeh 'bacon', crumbled tempeh bolognese and butter beans with feta, and says 'how to cook tempeh' could become a recurring content format.
They shift the challenge from persuading people to replace meat to making the ingredient the easiest addition to a meal they already enjoy.
Use large conversation datasets to challenge marketing stereotypes
Thompson tests a common marketing assumption against millions of social conversations, then reframes the audience around behaviours rather than age or decline.
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The method: name the myth, run the data through Sweet Spot's Insight Engine, and organise the findings into spending areas brands can act on.
The post challenges the myth that over-45s only want incontinence pads, Saga holidays and SunLife insurance.
Thompson says 8.9 million real conversations revealed reinvention: premium meaningful travel, smart home technology, wellness tracking, hobbies, side businesses and beauty spending for confidence.
The findings are attributed to Sweet Spot's Cultural Impact report.
AI shopping creates an earlier consideration moment brands must prepare for
Thompson describes an 'AI shelf' alongside the physical and digital shelf.
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They argue AI can interpret a shopper's real need, identify non-negotiables and surface a shortlist before the shopper reaches a search results page or store. Brands need to clarify the specific job a product does, the person and moment it suits, the language shoppers use for the problem, and the product information AI needs to judge fit.
Replacing a front-door handle: a broad search produced options, but the first handle was wrong by about 2mm.
Feeding photos and measurements into ChatGPT helped identify the relevant criteria—plate height and width, screw centres, keyhole and PZ measurement, spindle size and finish—and narrow a large pool to compatible options.
Thompson also uses the term GEO, or generative engine optimisation.
AI output needs human checking, especially if entry-level roles disappear
Thompson argues that ChatGPT hallucinates and every output needs a human to judge whether it is right, makes sense and has enough context.
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They ask who will do that checking if entry-level opportunities disappear, since those roles are where people learn judgement and intuition. They say they are building their own AI tool while making this argument, and frame AI as a tool to improve human potential rather than replace the process of developing it.
A news story about entry-level jobs being taken by ChatGPT prompted the post. Thompson notes that Gen Z and their nine-year-old son are growing up tech-savvy, and asks whether future entry-level jobs will be 'AI-Checker' or 'Prompt Engineer'.
A specialist network, not a big agency, is the priority for CPG growth work
Thompson describes Sweet Spot as a joined-up team of specialists, not a big agency.
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They prioritise assembling operators with specific strengths and matching them to projects as briefs arrive, so the network can help each other win more of the right work. The post targets specialist consultants and freelancers rather than brands.
The invited strengths include retail sell-in and buyer strategy, distribution and wholesale growth, on-trade and foodservice access, international go-to-market, partnerships and channel deals, e-commerce growth across Amazon and DTC, and fundraising or investor decks. Thompson asks people who have secured listings, opened new channels, increased rate of sale or scaled brands beyond the early hustle phase to send a direct message.
How do you turn social listening into something a business can act on, rather than a sentiment report?
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This post offers the clearest worked example.
Tina Louise Thompson traces a single case, Vaseline, from insight to results.
More than 3.5 million posts showed people using the product for things the brand did not invent, such as perfume tricks and leather shine.
The commercial return followed: 63.3 million interactions, retail sales value up 13.9%, and e-commerce sales up 43% within a month.
Thompson emphasises the work between listening and results: the brand tested the hacks, validated the safe and useful ones, debunked the rest, and only then built them into a platform, Vaseline Verified.
Their point is that most businesses are not structured to hear consumer behaviour commercially, leaving insights unvalidated and unclaimed.
For brands planning a campaign
Use this to argue for funding a validation stage, not just a listening dashboard. A brand should ask which consumer behaviours in its category are already public, who is responsible for testing them, and which platform could carry the validated ones.
How does a social trend become an in-store merchandising decision?
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This post follows the shift from observed shopper behaviour to retail execution.
Thompson describes the Picnic Sunshine Basket trend, where shoppers build gift-style edits of bright, coordinated products.
They argue that colour blocking is well established in beauty and wellness but underused in grocery.
Their proposal is specific: create a yellow-led sunshine fixture that signals gifting and occasion without explanation; merchandise cross-category blocks of snacks, drinks and small gifts so shoppers build baskets rather than browse; and stretch one colour concept across teacher gifting, get-well-soon, picnics and summer hosting.
Thompson says this needs no new product, only better storytelling with existing assets, and names grocery retailers where the execution could land.
The post draws on a consumer trends report built from 62 million data points across social and search behaviour.
For brands planning a campaign
This is a template for a retail activation brief: one colour or mood concept, multiple seasonal moments, cross-category blocks, and no new product development. A brand could give a retailer a single fixture idea instead of a promotion.
How do you read category sales data and come back with a different brief rather than a new campaign message?
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This item traces the reasoning from numbers to creative strategy.
Thompson separates two things often reported as one story.
UK unit sales of beans, pulses, tofu and tempeh rose 7.3% in the first half of 2026, while plant-based meat alternatives fell 4.3%.
Within those figures, tempeh sales were up 71.5%, dried beans, peas and lentils up 16.7%, and premium canned and jarred butter beans up more than 30%.
Thompson's reading is that consumers are not rejecting affordable plant protein; they are moving away from products imitating meat toward ingredients they already understand.
They propose 'food layering', where the healthy element sits alongside the comforting one rather than replacing it, and note that tempeh's versatility makes 'how to cook tempeh' a recurring content format rather than a one-off product demonstration.
Thompson reframes the question from 'how do we persuade people to replace meat?' to 'how do we make this the easiest, most desirable thing to add to a meal they already enjoy?'
For brands planning a campaign
For a food brand, this is a reason to test an addition-to-meal message against a replacement message, and to plan recipe content as a franchise with repeat formats rather than a single launch push.
What does Thompson's research method look like when applied to a widely held assumption?
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This post shows the approach and the output it produces.
Thompson takes a stated consumer myth—that anyone over 45 is only thinking about retirement, health issues and insurance—and tests it against 8.9 million real conversations run through Sweet Spot's Insight Engine.
Instead of decline, they report five themes: premium, meaningful travel such as foodie walking tours and boutique cruising; smart home technology; wellness tracking through sleep rings and health wearables; hobbies and creative tools; and side-hustle or second-act businesses.
Thompson also notes beauty spending focused on confidence now rather than looking younger, and describes the group as spending on their own terms.
The findings are attributed to Sweet Spot's Cultural Impact report.
For brands planning a campaign
The value here is a repeatable format: name a category assumption, test it against a large conversation set, and publish the reframe. A brand with an ageing or neglected buyer segment could commission the same exercise as a positioning input.
How is shopping behaviour changing before a customer reaches a shelf or a search results page?
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This post explains the shift and what it demands of brands.
Thompson builds the concept from their own experience replacing a front-door handle.
A broad search gave them many options, but the first handle they ordered was wrong by about 2mm.
Feeding photos and measurements into ChatGPT helped them identify the criteria that actually mattered: plate height and width, screw centres, keyhole and PZ measurement, spindle size, and finish.
Thompson's point is that AI creates an earlier moment of consideration.
Before a shopper compares products across a physical or digital shelf, AI can interpret the real need, identify the non-negotiables and surface a small shortlist.
They argue brands now need clarity on the specific job a product does, the person and moment it suits, the language shoppers use for the problem, and the product information AI needs to judge fit.
Thompson also uses the term GEO, for generative engine optimisation.
For brands planning a campaign
This is a prompt to audit product data for machine readability: does the page state the job the product does, who it is for, and the exact terms a shopper would use? It affects content and data work, not just media spend.
What is Thompson's position on the limits of the tools they sell around?
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This item offers a counterweight to their AI-shelf argument.
Reacting to a news story about entry-level jobs being taken by ChatGPT, Thompson argues that AI output still needs human checking: whether it is right, makes sense and has enough context.
They ask who is doing that checking and what happens to the judgement and intuition of people who never get an entry-level role to learn in.
Thompson notes that they are building their own AI tool while making this argument, and frames AI as something that should improve human potential rather than replace the process of developing it.
For brands planning a campaign
Useful when a brand is deciding how much human review to build into an AI-assisted insight or content process. It argues for named reviewers and defined checking responsibilities rather than straight-through automation.
Tina Louise Thompson uses the Vaseline example to argue that 3.5 million organic posts amount to unpaid consumer R&D, not just brand chatter.
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The brand found beauty hacks, perfume tricks, leather shine, and everyday fixes; it tested useful hacks, debunked unsafe or unsuitable ones, and turned the behaviour into a platform called Vaseline Verified. The post cites 63.3 million interactions, 13.9% retail sales value growth, and 43% e-commerce sales growth within a month.
Starts with public consumer behaviour, validates or rejects specific hacks, then turns the strongest behaviour into a named platform with commercial metrics.
For brands planning a campaign
For food and beverage brands looking to turn social listening into retail activation, Tina Louise Thompson can build a brief around existing consumer behaviour rather than a new brand story. Ask them to validate the behaviour, identify what should be debunked, and map a route from social listening to a campaign or retail platform.
In a post on 45+ consumers, Tina Louise Thompson says Sweet Spot’s Insight Engine analysed 8.9 million real conversations and found reinvention rather than decline.
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They challenge the idea that over-45s want only incontinence pads, Saga holidays, and SunLife insurance, and identify travel, smart home technology, wellness, hobbies, side businesses, and beauty as active spending areas. The post draws on Sweet Spot’s Cultural Impact report.
Uses a large social-conversation dataset to debunk a marketing stereotype, then organises the findings into buying behaviours brands can act on.
For brands planning a campaign
Useful for brands that need a sharper audience story than age-based stereotypes. A brief can ask for the size and source of the conversation data, its category implications, and the specific retail or marketing action that follows from the reframed audience.
Tina Louise Thompson argues that the grocery trade underuses colour blocking and cross-category merchandising.
Read more
The Picnic Sunshine Basket shows how colour can guide shoppers in store, with yellow-led sunshine fixtures signalling gifting, mood, and occasion.
The post recommends cross-category blocks of snacks, drinks, and small gifts to increase basket value, and says one colour-coded concept can extend across teacher gifting, get-well-soon, park picnics, and summer hosting.
It cites a 2026 Consumer Trends report built from 62 million data points across social and search behaviour.
Turns an online lifestyle trend into a physical and digital merchandising concept, using colour to organise the offer and build baskets.
For brands planning a campaign
Food and beverage brands looking for retail activation ideas can assess Tina Louise Thompson’s merchandising concepts, which link social trends to store execution and basket value. Ask what supports the trend, which cross-category products are involved, and how the concept would work in a named retailer or seasonal window.
Tina Louise Thompson argues that plant-based is not dying but losing the disguise.
Read more
The post cites UK sales data for the first half of 2026: unit sales of beans, pulses, tofu, and tempeh rose 7.3%, while plant-based meat alternatives fell 4.3%.
Tempeh sales rose 71.5%, dried beans, peas, and lentils rose 16.7%, and premium canned and jarred butter beans rose more than 30%.
The recommendation is food layering: add protein and fibre alongside meals people already enjoy rather than persuading them to replace meat.
The post gives recipe formats such as smoky tempeh “bacon,” crumbled tempeh bolognese, and butter beans with feta, and proposes “how to cook tempeh” as a content franchise.
Combines category sales data with food-layering recipes, then turns the product into repeatable content formats.
For brands planning a campaign
Food and beverage brands can use this example to assess how Tina Louise Thompson reframes an innovation or marketing brief around addition, not replacement. Ask for the data source, specific product formats, and a content platform that makes the ingredient easy to add to existing meals.
Tina Louise Thompson describes an “AI shelf” alongside the physical and digital shelf.
Read more
In a personal example about replacing a front-door handle, they explain that a broad search produced options, but the first handle was wrong by about 2mm.
They then used ChatGPT with photos and measurements to identify plate height and width, screw centres, keyhole position or PZ measurement, spindle size, and gold finish.
AI helped translate the need into criteria and narrow a large product pool to a relevant shortlist.
For FMCG brands, the question is whether AI would understand when a product is the right answer.
That requires clarity on the specific job the product does, the person, mission and moment, the language shoppers use, and the product information AI needs.
Uses a personal, low-glamour problem as a miniature case study, then applies the pattern to FMCG search and product information.
For brands planning a campaign
Brands preparing for AI-assisted discovery or e-commerce can ask Tina Louise Thompson to work on shopper language, product information, and category criteria. Test whether the brand’s products are described in terms an AI tool can use to judge fit.
In a post about AI and entry-level jobs, Tina Louise Thompson says AI is cheap, but cutting entry-level roles costs businesses the next generation of experience.
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They warn that ChatGPT hallucinates and still needs human checking, and ask who will do that checking if entry-level opportunities disappear.
The post mentions Gen Z and their nine-year-old son growing up tech-savvy.
Although they are building an AI tool, they stand by human potential, with AI as a tool.
Opinion-led commentary connects a current news item to personal experience as a small business owner and AI-tool builder.
AI and work commentary, rather than a documented retail or category-growth method.
For brands planning a campaign
This is relevant to employer brand, future-of-work, or AI-adoption conversations rather than direct retail activation. Ask Tina Louise Thompson for a balanced view of AI use that covers human judgement, checking, training, and talent development.
Tina Louise Thompson describes Sweet Spot as a joined-up team of specialists that helps grow CPG brands, rather than a big agency.
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In a post aimed at specialist consultants and freelancers, they invite people with expertise in retail sell-in and buyer strategy, distribution and wholesale growth, on-trade and foodservice access, international go-to-market, partnerships and channel deals, e-commerce growth across Amazon and DTC, and fundraising or investor decks. They ask people to message directly if they have secured listings, opened channels, increased rate of sale, or scaled brands beyond the early hustle phase.
Builds a bench of specialist operators around client needs and matches them to projects as briefs arrive.
For brands planning a campaign
A brand can consider Tina Louise Thompson as a route to a network of CPG operators, not just an individual content creator. Ask who would own the work, what each specialist can show about secured listings or channel growth, and how the network would coordinate delivery.
Across the posts here, a recurring format pairs a striking claim with data or a specific example, several bulleted observations, a commercial implication, and a question or next step.
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Subjects range from social listening, consumer myths, retail merchandising, and plant-based ingredients to AI shopping and AI and work. Concrete examples include Vaseline hacks, the Picnic Sunshine Basket, UK plant-based sales data, the 45+ conversation study, and the door-handle measurement story.
Opens with a clear claim, uses data or a lived example, turns the observation into a business question, and often invites a comment or message.
The posts here do not carry individual post dates, so this describes a cross-post pattern rather than a dated sequence.
For brands planning a campaign
A brand should expect written recommendations for operators that end with a testable retail, innovation, or campaign action—not general trend commentary. Ask for the source data, the specific category application, and the next step that can be briefed to a team.
Tina Louise Thompson's posts document a working connection to Sweet Spot, the CPG specialist team they describe with first-person language such as 'we' and 'our.' Ask them to clarify whether the relationship is ownership, employment, or a client/partner arrangement.
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No other client, sponsor, affiliate, investor, or owned business is named. Brands such as Vaseline, Tesco, Asda, Waitrose, Sainsbury's, Morrisons, Belvoir Farm, Pipers Crisps, PROPER SNACKS, and ChatGPT appear as case studies, retail examples, or tools rather than disclosed commercial relationships.
Sweet Spot
Disclosed partnership
Tina Louise Thompson writes about Sweet Spot in first-person terms: 'Sweet Spot has never been a big agency model.
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We operate as a joined up team of specialists to grow CPG brands,' and refers to 'our Sweet Spot Insight Engine' and 'Sweet Spot's Cultural Impact report.' The posts don't establish whether they own, work for, or partner with the business; ask them to clarify their relationship to Sweet Spot.
Tina Louise Thompson writes about how consumer behaviour surfaces before brands act on it.
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Their posts move from social listening to retail execution: Vaseline hacks become a validated brand platform, a colour-led picnic basket becomes cross-category grocery merchandising, plant-based sales data becomes food-layering recipes, and a door-handle problem becomes an argument about the AI shelf.
Start with the Vaseline post for the listening-to-validation method, then read the Picnic Sunshine Basket and plant-based posts for retail activation, followed by the AI shelf post on product information and AI-assisted discovery.
The specialist-network post explains how they work with CPG operators and what expertise they look for.
Both track how AI is changing product discovery and retail.
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Max Sinclair's posts on OpenClaw and Walmart's AI shopping agent Sparky cover the same shift Tina Louise Thompson calls the AI shelf: brands must make product information legible to AI systems that recommend products.
Sinclair focuses on agentic commerce, platform rules and seller tactics, often through fast news analysis. Thompson starts with consumer conversation and category trends, then translates them into FMCG merchandising and innovation briefs.
Both use consumer behaviour to explain retail and category shifts.
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Ryan Graham Donald's posts on Checkers Sixty60 and Bootlegger analyse how a service becomes part of routine and how a business model must change behind the scenes. Thompson applies a similar habit-and-behaviour lens to FMCG categories, social listening and retail merchandising.
Donald writes longer business-model case studies, mainly about South African grocery, forecourt and hospitality brands. Thompson focuses on CPG and FMCG trend data, social listening and short, practical marketing recommendations.
Both turn consumer observation into a repeatable method.
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Ashley Daisley's CAMPFIRE posts on Amazon Fresh and a P&G retail safari show how to test whether a brand story is understood and felt. Thompson tests consumer myths against large conversation datasets and turns the findings into retail or campaign actions.
Daisley's approach is workshop-led and framework-driven, aimed at founders and brand teams. Thompson's is data- and trend-led, aimed at CPG and FMCG operators, with an emphasis on social listening and category merchandising.
Tina Louise Thompson has 4,629 LinkedIn followers, observed 8 October 2026.
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Their posts speak directly to CPG/FMCG brand, category, insights and shopper-marketing professionals, using retail and commercial language such as listings, rate of sale, basket value, category growth and e-commerce.
For a food and beverage brand looking to turn social-listening insight into retail activation, this is a relevant but small practitioner audience—not consumer reach or a distribution channel.
Before committing to a reach-based placement, ask Thompson for LinkedIn follower demographics by geography and job seniority/function.
If a campaign depends on specific audience demographics, also ask for recent performance on comparable topics to assess reach and engagement against current data, not follower count alone.
None of Tina Louise Thompson’s posts sets out a published sponsorship programme, media kit, rate card, or format menu for brands.
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They describe a collaboration model built around Sweet Spot, which Tina calls a joined-up team of specialists that grows consumer-packaged-goods brands rather than a large agency.
In one post, Tina invites specialist consultants and freelancers in retail sell-in, distribution and wholesale, on-trade and foodservice, international go-to-market, channel partnerships, ecommerce across Amazon and DTC, and fundraising to make contact so they can bring them into client work when the right client need arises.
That points to a scoped consulting or project arrangement rather than a standard creator sponsorship.
Buyers should agree on the terms, deliverables, pricing, objective, and timeline directly with Tina before assuming anything about availability, cost, or turnaround.
Good fit: a food or beverage brand wants to turn existing social conversation into a retail activation, without starting from a new product launch.
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Tina Louise Thompson’s Vaseline example traces a useful path from listening to action: identify consumer-created uses, test which are safe and useful, and build the validated behaviour into a campaign platform.
The Picnic Sunshine Basket post then shows how an observed trend can become a grocery idea: use a clear colour theme to group snacks, drinks, and small gifts around occasions, so shoppers can build a basket across categories.
For a campaign aimed at turning social conversation into a retail activation, ask Tina to specify the source behind the trend, the behaviour to validate, the retailer and seasonal occasion, and how success would be measured.
Tina’s posts support a strategy or consulting discussion; they do not establish a standard sponsorship package or published deliverables.
Tina’s LinkedIn following is 4,629, not proof of consumer reach or follower demographics.
When to choose a specialist
Poor fit: a brand wants a large consumer-reach placement with guaranteed impressions, a standard creator rate card, or a ready-made sponsored video package.
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Tina’s posts do not specify what formats, pricing, audience demographics, or performance figures are available for comparable placements.
It would also be a weak fit to ask for a campaign whose main task is promoting a meat substitute as a direct replacement for meat.
In the plant-based post, Thompson argues for adding familiar ingredients to meals people already enjoy, rather than leading with replacement.
That perspective could still help a brand willing to test an addition-based message, but it does not match a campaign aimed at replacement positioning.
A worked campaign example
Hypothetical scenario: a grocery brand has social-listening evidence that shoppers are assembling bright, gift-like summer edits and wants to increase cross-category basket value without developing new products.
A useful first engagement would ask Thompson to turn the observed behaviour into a testable retail concept.
Working angle: build a “sunshine basket” around a yellow visual cue, grouping the brand’s drinks and snacks with complementary small gifts for a named occasion such as park picnics or summer hosting.
First check that the listening supports the behaviour and that the proposed products and occasion fit the retailer.
Then define a pilot store or fixture, the participating categories, and measures such as units per basket and cross-category sales against a suitable comparison.
This follows the route in Tina’s post from trend observation to colour-led in-store navigation and basket building.
The retailer, products, test design, and results would need to be agreed with the brand.
Choose Max Sinclair when a food and beverage brief shifts from social listening to AI-mediated shopping and product discovery.
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Their posts cover AI agents that handle routine purchases, Walmart tightening product-title rules so AI can parse products, and what brands must do to be recommended inside AI shopping tools.
For brands asking how to be visible and correctly described in AI-driven e-commerce, they address that specific decision.
They are not a substitute for consumer-conversation research.
Their evidence focuses on AI infrastructure, retail platform rules and agentic commerce—not mining social listening for consumer language, hack cultures or category occasions.
Brands that need to start with what shoppers are already saying will need that research elsewhere.
Their material also draws on fast-moving platform changes, so recommendations may date quickly.
Choose Ryan Graham Donald when a brand wants to frame retail activation as a business-model and habit-change question rather than a social-listening output.
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Their posts analyse Checkers Sixty60 changing grocery habits and Bootlegger building a scalable coffee business through manufacturing, franchising and channel choices.
For food and beverage brands looking to translate a consumer trend into category growth, they offer examples of how convenience, routine and behind-the-scenes operations determine whether an activation becomes repeatable.
They are a better fit when a campaign needs strategic comparisons of retail models or category structure.
Their posts do not show social listening as an input.
They are retrospective business case studies, not a method for collecting or interpreting consumer conversation.
Brands that need to validate a trend using social data will need that research elsewhere.
Their analysis is also more macro, with examples focused on South Africa.
Choose Ashley Daisley when a team needs to turn consumer insight into a shared internal decision before committing to a retail activation.
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Their posts describe facilitated workshops that surface what data cannot, an Echo Check for whether an organisation tells one coherent story, and a Reality Check retail safari that sent brand teams into direct-to-consumer stores. For food and beverage brands whose social listening reveals a trend but whose internal teams disagree on what it means, they are well suited to aligning the people who will act on it.
Their posts centre on innovation workshops, brand positioning and retail-store experience—not social listening as a data source or grocery merchandising mechanics.
Brands seeking a ready-made retail activation idea or basket-building tactic will need to develop that separately.
Their material also promotes their own framework and workshop offer, so it is not an independent review of what works.
Seven public LinkedIn posts by Tina Louise Thompson discuss CPG specialist networks, social listening, consumer trend research, retail merchandising, plant-based food data, AI-assisted shopping, and AI and work.
The posts do not show individual post dates, so they support current themes rather than a dated sequence.
They do not establish complete lifetime coverage, a signature book, show or earlier body of work.
A LinkedIn account snapshot dated 8 October 2026 shows follower count and account details.
