Resource Type: Article

  • QualMinds and the rise of Ai moderation – part 2

    QualMinds and the rise of Ai moderation – part 2

    By ICG member Hugh Carling

    Hot (ish) on the heels of the ICG’s fascinating panel on AI,  QualMinds was launched.

    Expert views on hot topics

    QualMinds is a small panel of expert independent researchers who each month will be sharing their views on a topical question about the developments shaping qualitative research, particularly around AI. It features:

    We’re using Liveminds Now to capture, curate and share the experts’ views in a short video report each month.

    AI tool wish list

    In the future, what AI powered research product or feature would you most like to see developed and why? We asked our QualMinds panel of ICG members, and they shared a fascinating wish list (sadly not available in time for Christmas…)

    Their ideas include:

    – AI with “bionic memory” for deeper analysis
    – Culturally aware AI
    – Tools for better visual storytelling
    – Holistic innovation platforms
    – Truth telling in participant screening

    You can hear highlights of their ideas in full in this video.

     

    (Earlier video: How do you feel about the rise of AI-mediated moderation? here)

     

  • Christmas Traditions in Behavioural Science Terms

    Christmas Traditions in Behavioural Science Terms

    Written by ICG member Iona Carter, as part of a series of posts she’s writing on LinkedIn.

     

    Phil Barden (of DECODE marketing) and I teamed up this year to look at 12 Christmas traditions through the lens of behavioural science.

    I’ve selected a couple here to share, but if you’re interested in having a look at all 12 – you can see them in my profile on LinkedIn

    https://www.linkedin.com/in/iona-carter-cmrs-96b6214/

    I’ve chosen to share Days 1 to 3 for you here.  Hope you find them interesting and put you in the mood for the festivities to come

    THE FIRST SEASONAL TRADITION is… Gifting

    Christmas isn’t Christmas for many of us without the giving and receiving of gifts: a tradition rooted in a rich blend of Christian theology, ancient pagan festivals and modern customs.

    THE BESCI PRINCIPLE:

    There are many, many behavioural science principles that are reflected in the giving and receiving of gifts, but we’ve chosen to talk about  The Warm Glow / Impure Altruism Effect which describes the positive emotional reward people feel when they act generously or do something good.

    In other words, it isn’t just about the joy of opening our own gifts, it’s also about the reward we feel knowing that others will enjoy the gifts we give them (a 5-pack of underpants, or a badly knitted jumper notwithstanding!).

    Neuroscience studies have shown that the act of giving to meaningful others activates reward-related brain regions.

    WHERE DO WE SEE THIS IN MARKETING?

    We frequently see brands and retailers using phrases like “give joy”, or “share the magic” in their advertising which trigger the concept of the joy of giving in our minds.  This year, we’ve seen Stacy Solomon starring in the AbbotLyon Christmas ad., which perfectly encapsulates the warm glow effect.

    https://www.facebook.com/AbbottLyon/videos/1367582338292559/

    THE SECOND SEASONAL TRADITION is The Advent Calendar.

    Its origins are typically traced back to the early 1800s, when German Luthereans prepared for, and anticipated the marking of the birth of Christ by deploying countdown practices such as lighting a candle or marking chalk marks on doors or walls.  The, now ubiquitous, chocolate calendars didn’t become popular until the early-mid 20th century.

    What began as a spiritual timer has become one of retail’s most powerful rituals of daily reward and rising excitement.  Advent Calendars work because they turn the waiting into the main event (obviously helped by a series of mini-rewards along the way).

    THE BESCI PRINCIPLE

    So, for the Advent Calendar, we’ve chosen to talk about The Anticipation Effect which describes how the brain often gets more pleasure from the expectation of a reward than from the reward itself.

    In neuroscientific terms, dopamine rises in advance of the outcome, which is why waiting, wondering, and counting down can feel as emotionally powerful as the moment of reward itself.

    WHERE DO WE SEE THIS IN MARKETING?

    We think @Aldi have got the anticipation effect all sewn up with their 2025 Christmas advertising campaign which celebrated Kevin’s 10th anniversary with a three-part romantic saga from proposal, through a chaotic stag do (and dare I say, a more refined hen do), culminating with Kevin and Kate’s marriage. And all this supported by a combination of integrated messaging across platforms, the obligatory merchandise (have you got your Caulidog yet?) and clever references to classic Christmas movies.

    https://www.youtube.com/watch?v=RaF1fzzfM74

     

    THE THIRD SEASONAL TRADITION is The Christmas stocking

    A tradition with many suggested origins and cultural variation, it’s widely believed to be rooted in the story of St Nicholas secretly dropping bags of gold coins down a chimney for three poor sisters, with the gold landing in their stockings (or shoes) that were hung by the fire to dry.

    So, the Christmas stocking symbolised quiet generosity long before it became the temporary home of chocolate coins and novelty gifts. By now, it has, become an annual source of excitement and anticipation for young children and adults alike.

    THE BESCI PRINCIPLE

    For the Christmas stocking tradition, we’ve chosen to talk about Emotional Memory Encoding…

    … which is the process by which experiences paired with strong emotion e.g. excitement, joy, anticipation are stored more deeply and durably, and recalled more easily, in the brain than neutral ones.

    When a ritual like the Christmas stocking is repeated every year in childhood, it becomes a lasting emotional shortcut to how Christmas feels, not just what it is.

    WHERE DO WE SEE THIS IN MARKETING?

    There are so many examples of brands and retailers reactivating those first emotional rituals of Christmas,  it’s hard to pick just one!

    The most obvious and literal, of course, being the proliferation of Christmas Stockings (with variable contents) aimed at adults, and which tap into those early memories of excitement and joy in order to make the ‘gifts’ inside feel irresistible.

    But we couldn’t leave out this year’s @JohnLewis Christmas ad. which, amongst other things,  capitalises on emotional memory encoding by reconnecting viewers with the feelings of youth, caring for others, and identity. It doesn’t sell a gift — it reactivates a memory of who you were and who you still are at Christmas.

    https://www.youtube.com/watch?v=z1bRlnyQeDk

  • The Symphony within the Data – Composing Insights with AI

    The Symphony within the Data – Composing Insights with AI

    Article by ICG member Arthur Fletcher

     

     

     

     

     

     

     

     

     

     

    Using Collaborative AI* to produce a research report is, in many ways, like composing a beautiful symphony.

    It begins with the interviews themselves: the raw conversations, the stories, the hesitations, the sparks of emotion. These are your musical materials – keys, chords, motifs, riffs and phrases.  Each participant offers a new timbre, a different rhythm, a subtle variation on the theme.  By the time fieldwork ends, you have an orchestra’s worth of material waiting to be shaped.

    For a typical AI analysis, the next step is an analysis plan: an executive summary, a thematic breakdown, key quotes, implications etc.  This is immensely valuable but it can feel like a pianola roll – a predetermined script that produces a pleasant, recognisable tune.  It follows familiar combinations and harmonic progressions and it gets the job done but it is not yet a symphony. It has form, but not soul.

    This is where Collaborative AI changes the creative atmosphere.

    The AI takes that pianola roll – the structure, the patterns, the first implications – and lays it out clearly.  Then, like a composer settling at the piano, you begin to explore. You start asking questions of your data:

    “What happens if I follow this theme?”

    “Where does this emotional progression lead?”

    “What is the story hiding beneath this discord?”

    The AI listens, responds and plays back possibilities.  It doesn’t invent notes that were never played, it helps you uncover the melodies the data is already singing.  It can isolate a phrase from one interview, harmonise it with a counter-theme from another or spotlight a discord that demands resolution.  It allows you to roam through your material with freedom, curiosity and confidence, guided but never constrained.

    Slowly, the music becomes richer.  Insights that were once scattered become aligned. Subtle tensions resolve into understanding.  A fleeting remark becomes the emotional centrepiece of the movement.  What began as raw notes and mechanical playback transforms into something shaped by instinct, interpretation and craft.

    And then – almost imperceptibly – the final composition emerges.

    Not a machine-generated tune, not a formulaic analysis but a symphony – layered, resonant, human in its sensitivity and unmistakably yours.

    Collaborative AI does not replace the researcher, it accompanies them.  It provides the structure of the composition, the clarity of the score and the responsiveness of an intuitive musical partner.  But the symphony – the insight, the narrative arc, the emotional truth – is composed by the human hand.

    In this way, Collaborative AI doesn’t diminish the artistry of qualitative research.  It amplifies it, offering researchers the chance to move beyond mechanical summaries and into the realm of genuine creative interpretation.

    Because when AI and researcher compose together, insight can finally sound as beautiful, as powerful, and as unforgettable as music.

    If you would like to know more about Collaborative AI*, please get in touch.

    *’Collaborative AI’ is a term I’ve coined to describe an AI that works with the researcher rather than in their place – an intelligence that supports, clarifies and elevates human interpretation while remaining absolutely faithful to the data.

    AI also helped me to create this article.

    Arthur Fletcher | LinkedIn

  • What Do Teachers Really Think About the Curriculum & Assessment Review?

    What Do Teachers Really Think About the Curriculum & Assessment Review?

    Article by ICG member Jill Elston, Insightful Research 

    When the government published its long-awaited Curriculum and Assessment Review on 5th November 2025, the reaction from unions, subject associations and education organisations was immediate and vocal. But what about the teachers and school leaders who will actually be implementing these changes in classrooms across the country?

    We decided to find out. Within days of the Review’s publication, we surveyed over 100 education professionals to capture their initial reactions whilst they were still fresh. This was a deliberate departure from our usual approach (we typically conduct in-depth, nuanced qualitative research with schools). However, this moment called for a quick temperature check to understand sector sentiment before moving on to more detailed exploration.

    Who we spoke to:

    • Headteachers, senior leaders and heads of department

    • Staff from academies, MATs and local authority schools

    • Primarily secondary teachers, with some primary representation

    Whilst not statistically representative, this research provides a timely snapshot of views from those at the chalk-face.

    The headline verdict? Cautiously optimistic, but with significant concerns.

    What teachers welcomed:

    • Reduced emphasis on EBacc: seen as offering greater flexibility for creative and vocational subjects

    • Promise of less exam content and exam time: reducing student stress and curriculum overload

    • Modernisation of the curriculum: particularly digital literacy, financial literacy and oracy

    • Evolution rather than revolution: 48% felt the amount of change proposed was “about right”

    Overall, 54% had a positive reaction to the proposals. Teachers told us they were pleased to see many of their long-standing hopes reflected in the Review.

    But concerns run deep:

    However, 43% had mixed feelings, and 57% felt the Review hadn’t fully captured all the issues schools face. When we dug deeper, persistent worries emerged:

    • Teacher workload: the number one barrier to implementation (cited by 65% of respondents)

    • Insufficient funding: the second biggest concern (61%)

    • Staff recruitment and retention: particularly acute for Triple Science and Computing (52%)

    • The enrichment accountability announcement: many feel positive curriculum changes will be undermined by new demands

    Analysis revealed that many concerns related to funding, inspections and workload which were issues outside the Review’s Terms of Reference. This highlights an important truth: curriculum reform is just one piece of a complex jigsaw.

    What schools will need in the near future

    As schools move from reaction to planning mode, our research points to significant demand for support.

    Teachers told us they’ll need:

    Most in demand

    • Clear, practical implementation guidance (42%)

    • New or updated teaching and learning resources (40%)

    • Subject-specific training and CPD (36%)

    • Digital and online teaching resources (34%)

    Growing areas of interest

    • Curriculum planning tools and frameworks

    • New assessment materials

    • Support in delivering enrichment programmes (15%)

    • AI-enabled resources for marking, assessment and resource creation (13%)

    This presents clear opportunities for education suppliers, publishers and training providers who can genuinely support schools through this transition.

    Download the full report below to explore these findings in detail, including what different types of schools said, specific subject concerns, and the barriers they anticipate. Whether you’re developing products and services for the education sector, working in policy, or leading a school through these changes, this research offers valuable insight into how teachers and school leaders are responding to one of the most significant curriculum reviews in a generation.

    Planning your response to the curriculum review? We can help you understand what teachers and school leaders actually need to make implementation successful. Contact us to explore how research can inform your next steps.

  • Graham Booth on Research & Creative

    Graham Booth on Research & Creative

    ICG member Graham Booth is this week’s guest on Peter Spear’s Podcast, ‘That Business of Meaning.‘

     

     

     

    They cover a wide range of issues related to the application of qualitative research in the development of effective brand strategy and communications.

    LISTEN HERE 

    LinkedIn post here 

  • Cxoice Survey Platform Extends to Include Real-Time Video Capture

    Cxoice Survey Platform Extends to Include Real-Time Video Capture

    By ICG member Saul Dobney.

    The Cxoice Survey Platform (run by Saul Dobney, ICG member) has been extended to include real-time video capture as someone completes a survey; together with speech-to-speech AI and conversational AI capabilities. This means participants can talk to the survey as they complete it, to explain their reasoning, or so you can see their reactions to prompt materials. The benefit is quant data with added transcriptions for commentary, and video show people can show you things.

    Video with quant might seem a strange idea for researchers who only use traditional tick-box questionnaires. However, for surveys that ask people to do visual tasks like marking up a webpage, or asking for participant to show their preferences, or to collect reactions to new marketing materials, then the combination of video and speech allows respondents to ‘show you’, not just ‘tell you’.

    It also works for video-based tasks – for instance show me the cosmetics you use, or show me how you load a washing machine.

    With all the issues over data-quality and the need for researchers to go deeper and to provide research that can’t be done with AI, video has the potential to have a much bigger role in all types of research projects.

    Saul Dobney | LinkedIn

  • Why Personas Are About to Become More Central to Research than Ever Before

    Why Personas Are About to Become More Central to Research than Ever Before

    Article by ICG member John Habershon

     

     

     

     

     

     

     

     

    Personas have been the quietly powerful output of qualitative research – often created, presented, then set aside as merely interesting additions. I believe AI will transform personas from being a nice-to-have deliverable into what they’ve always promised: the central organising principle for understanding brand value and the roadmap for targeted marketing.

    The process of creating personas – identifying patterns and clustering participants into meaningful groups – is a key creative analytical skill of qualitative researchers. But it is also a core strength of AI.

    How do we exploit the power of the new AI tool whilst maintaining our qualitative skillset?

    The Traditional Art of Persona Creation

    Creating personas has always been one of the most satisfying aspects of qualitative research. It’s where analysis transforms into recognition – that moment when a client sees a set of consumers reflected in a persona you’ve uncovered. When each persona sparks genuine recognition from customer-facing people in sales and marketing you know you’ve captured something real.

    The process exemplifies what we achieve through rigorous creative thinking and human empathy.

    But the traditional process has always had limitations: time constraints, restricted sample sizes, and the sheer cognitive load of pattern-matching across dozens of interviews.

    Case Study 1: Plant-Based Meat – Human vs AI

    A couple of years ago I conducted research testing six advertising images and product propositions for plant-based meat.

    Based on interviews with consumers with families, I created five personas by hand:

    ‘Trad’

    ‘Reducer’

    ‘Trialist’

    ‘Foodie’

    ‘Veggie’

    Recently I returned to the data, uploaded the 30 transcripts to Claude AI and asked it to create five personas.

    Here’s what emerged:

    ‘Traditional Sceptics’

    ‘Pragmatic Reducers’

    ‘Convenience Adopters’

    ‘Ethical Pioneers’

    ‘Curious Experimenters’

    The table below compares the two sets of personas side-by-side:

    Article content
    Manual/AI Comparison

    The AI identified the same core segments I had, but the differences made me re-examine my own thinking. There was no ‘Foodie’ in the AI set – on reflection, this was a small number in my sample that had made an impression on me personally. The same applied to the ‘Veggie’ category. Incorporating this under Ethical Pioneers made sense. Similarly, Foodie could be seen as a subset of Traditional Sceptics.

    What the AI added was rigour: it gave me the percentage of the sample for each persona and could list every respondent under each. It also identified crossovers and showed which respondents fit into more than one category.

    The AI’s approach was multi-dimensional, cross-referencing all the factors. This ensured each respondent was classified based on behavioural patterns, not single statements, creating robust, actionable personas.

    Case Study 2: Running Shoes – Where AI Changes Everything

    At just thirty half-hour interviews, the plant-based meat study was manageable. With careful investigation and imaginative reasoning, I could create personas by hand.

    But my running shoe brands project operates at an entirely different scale: 7,432 social media conversations from Twitter/X (27.3%), Reddit (68.6%), and compiled references (4.1%).

    The AI sorted through this data to create six male runner personas:

    ‘The Value Hunter”

    ‘The Max Cushion Comfort Seeker’

    ‘The Performance Optimiser’

    ‘The Brand Loyalist’

    ‘The Pragmatic Beginner’

    ‘The Durability Demander’

    For each persona, it provided detailed information on demographics, running profile, brand preferences, attitudes and motivations, purchase triggers, and pain points.

    To differentiate between personas, the AI looked for patterns across a extensive range of factors: purchase behaviour, running experience indicators, pain and injury language, product knowledge indicators, decision-making language, age and life stage clues, lifestyle and context signals, shoe rotation and collection behaviour, brand interaction patterns, emotional tone and language, durability expectations and complaints, and purchase channel preferences.

    It’s not just that AI manages huge volumes of data. It acts as an inference engine, drawing together comments, preferences and reported behaviour and making deductions in a Sherlock Holmes fashion. At this scale and complexity, achieving this manually isn’t just difficult – it’s inconceivable.

    Why Personas Could Become More Central

    This evolution in capability changes what’s possible. Here’s why I believe personas are about to become more central to research and strategy:

    1. Scale Meets Depth. We can now create robust personas from datasets that were previously impossible to analyse comprehensively. Very large datasets from multiple groups and interviews, social listening data (as in this case), customer reviews, customer support conversations – all become sources for persona development.

    2. Living, Evolving Personas. Traditionally, personas were created once and slowly became outdated. With AI-assisted analysis, personas could be continuously refined as new data is available, keeping them relevant and actionable.

    3. Enhanced Targeting and Testing. AI-generated personas aren’t just analytical outputs – they become active tools for testing concepts, messaging, and advertising before launch, as demonstrated in the LinkedIn articles below.

    Quantitative Analysis – Adding Even More Power

    Here is an example based on a huge dataset of 2,700 respondents with detailed verbatim responses from two open-ended questions. AI is invaluable in creating a coding frame for each question. But we can take it much further and get even more value from asking Claude to create a set of personas. It will analyse the verbatim comments from both open-ended questions and also include the data on age bands, gender, social grade, work status, household income, marital status, presence of children, tenancy type.

    Here is an example of one of the 12 personas

    Persona 4: Affluent Eco-Adopters

    Demographics

    • Age: 35-64 (primarily 35-54)

    • Size: 456 respondents (8.5% of sample)

    • Gender: Evenly split

    • Work Status: 73% full-time employed

    • Income: £75,000+ (£100,000+ for many)

    • Social Grade: Primarily A/B

    • Children: Mixed

    Defining Characteristics

    Affluent Eco-Adopters are actively investing in sustainable technology and products. They’ve purchased electric

    vehicles, installed solar panels, choose organic and sustainable brands, and view environmental responsibility as both

    personal obligation and increasingly good investment.

    This group largely continues their lifestyle with minimal disruption. Whilst noticing price rises, these haven’t forced

    significant behavioural changes.

    Verbatim Examples

    • “I’ve opted for an EV and try to be better on energy management around the home”

    • “I buy organic where possible, avoid fast fashion, and support local businesses. Money is not the barrier to

    sustainable living for me”

    • “I’ve not seen a real change other than prices rises. We’re fortunate to be in a position where we don’t have to

    make difficult choices”

    • “I am a lot more worried about high interest rates. I am saving a lot more and am very conscious of my spending”

    Key Insights

    • Financial capacity to align spending with environmental values

    • Early adopters of sustainable technology (EVs, solar, heat pumps)

    • View sustainability as investment rather than sacrifice

    • Some guilt or awareness of privilege regarding financial security

    The resulting 12 personas, could better be described as market segments since they are based on quantitative data. Being able to conduct further exploratory data analysis based on these segments is a major opportunity.

    Where This Takes Us

    Persona creation represents a perfect merger of human intuition and judgement, combined with AI rigour.

    Additionally, with the help of Claude we also have the scope to test communications against each segment, creating genuinely targeted advertising and marketing.

    https://www.linkedin.com/pulse/testing-concepts-without-conducting-interviews-john-habershon-phd-v4dwe

    https://www.linkedin.com/pulse/developing-testing-ads-without-conducting-interviews-habershon-phd-yq9qe

    The question is no longer whether AI can help create better personas, but how quickly researchers will embrace this capability to deliver insights that are both deeper and more immediately actionable.

     

    John Habershon PhD | LinkedIn

  • AI in MR: What We Learned from Our First Discovery Session

    AI in MR: What We Learned from Our First Discovery Session

    By ICG member Arthur Fletcher

    A huge thank you to all the members who joined our AI Discovery Session last week – one of the biggest turnouts we’ve had for a while.  Clearly AI is on everyone’s mind, whether you’re already experimenting with it, quietly curious or still wondering what all the fuss is about.

    The aim of the session wasn’t to convert anyone or declare AI ‘the future’, it was simply to understand where members are right now, find out what they want to know and see what the ICG can do to support members as AI becomes more visible in our day-to-day work.

    What’s worrying people?

    Many of you said you feel overwhelmed by the speed of change.  With dozens of tools appearing almost weekly, it’s hard to know where to start and establish which ones are safe, reliable and genuinely useful. Qual researchers in particular voiced concerns about the use of AI in their work and consequently losing nuance, accuracy or even the essence of respondent voices.

    Several members raised the big ethical questions:

    What can we (safely and securely) upload to AI tools?  What are the ramifications for GDPR compliance?  What are the MRS doing about it?

    The lack of clear, independent-friendly guidance is leaving many unsure about how to use AI responsibly.

    And of course, there’s the commercial angle. Some members have already had clients asking whether AI is being used and if that means research should be cheaper.

    What do members want?

    If there was one theme that ran through the whole discussion, it was confidence. Members want:

    • Plain-English explanations of what AI can and can’t do
    • Practical examples of how AI fits into real research workflows
    • Help evaluating tools without wasting hours testing everything
    • Clear guidance on ethics, GDPR and professional standards
    • Advice on how to talk to clients about AI without undermining expertise
    • Case studies – good ones and bad ones – to learn from

    In short: people want support, not hype.

    What’s the role for the ICG (and MRS)?

    There was strong appetite for the ICG to take a leadership role in helping members navigate AI safely and confidently. Suggestions included:

    • Clear guidelines on ethical and responsible AI use
    • Templates for disclosure statements and data protection
    • Training sessions at all levels
    • A shared resource hub with prompts, examples and tool reviews
    • Drop-in ‘AI surgeries’ for questions and troubleshooting
    • Regular updates on new developments
    • Collaboration with MRS to ensure consistency on standards

    Although the ICG should work in the interests of members, it’s the MRS who should carry the flag for the MR industry and determine guidelines, best practice and ethical use.

    What happens next?

    Based on your feedback we’re now shaping the remit of a new ICG AI Working Group. It will bring together enthusiasts, cautious explorers and sceptics alike – because the group will only work if every viewpoint is represented.

    Thank you again to everyone who contributed so openly and honestly. Your insights have set a clear direction for what the ICG should do next. Watch this space for details on how to get involved, upcoming activities and opportunities to help shape the guidance we develop together.  If you haven’t already volunteered to help, please contact Lucie manager@theicg.co.uk

    Arthur Fletcher, Author at The ICG

  • Motherdom’ by Alex Bollen – an Introductory Conversation

    Motherdom’ by Alex Bollen – an Introductory Conversation

    We were thrilled to invite author and researcher Alex Bollen to our members’ Book Group last week to talk about her book, ‘Motherdom.’

    Here’s the beginning conversation* where she talks about the book’s key themes of motherhood, social norms and cultural nuances over time, and specifically how this has shaped families and parenting today.

    Alex brings the rigour of her Insight training to this must-read book.

    #Motherhood #parenting #society #culture #insight #mrx

    (* attendees have been blacked out for anonymity).

    About the ICG’s Book Group

    Our Book Group meetings can vary in format from session to session; some welcome the author to runn a Q&A session, whilst others leave our members to critique the book ourselves.

    Please note that we want our Book Groups to be a safe space to explore – you can be assured that your contributions will never be shared outside of the meeting.

     

     

     

  • Beyond the Machine: Human Insight in the Era of Post-Editing

    Beyond the Machine: Human Insight in the Era of Post-Editing

    Article by ICG advertiser, The Language Factory.

     

     

    It’s tempting to ignore the value of humans in a world that increasingly relies on AI. Indeed, everywhere you turn, you’re invited to streamline, enhance and in some cases replace previously human tasks and processes with AI. But when it comes to one of the most human of experiences, communication, would you really completely trust AI to get it spot on?

    With AI translation in the mix, human expertise is more essential than ever to ensure high-quality, accurate, culturally-sensitive translations that are genuinely authentic and impactful.

     

    What is machine post-editing for translation?

    Machine translation post-editing services (MTPE) use expert, and crucially human, mother-tongue linguists to refine your AI-generated content to deliver a top-quality, culturally-nuanced final translation. This involves careful review of the materials for accuracy, tone and cultural sensitivity, along with the correct terminology and phrasing to ensure that your message resonates with your target audience.

    Machine translation post-editing is particularly crucial for highly-specialised fields such as market research, healthcare, legal and other technical sectors, where every word counts.

     

    The power of human insight

    The role of an experienced human linguist in post-editing is more than simply correcting errors from an AI translation. Human insight is indispensable to achieving a precise and culturally-attuned final translation, including:

    • Cultural insight: expert native translators understand regional sensitivities, idioms and humour, ensuring that every translation resonates with a local audience.
    • Emotional intelligence: specialist translators capture tone and intent – not just words – adapting content to evoke the same emotional response, whatever the language.
    • Ethical and brand integrity: human translators can identify bias, preserve brand voice and ensure that translations align with your brand values and sensitivities, something automated systems can’t replace.
    • Contextual decision-making: professional linguists interpret meaning beyond just the literal and recognise how context shapes meaning, especially when translating complex or creative text.
    • Source-text ambiguities: human linguists can identify and rectify ambiguities and errors in the source text that AI translation would simply replicate.

     

    Best practice for machine post-editing

    • Understand the project: clarify the purpose of the material – is it intended to inform employees, educate on technical issues or promote a new product? Understanding the project goal ensures that the tone, style and terminology resonates with the target audience.
    • Use reference materials: leverage supporting documents to help translators understand industry-specific terminology or complicated concepts, especially for technical or highly specialised content.
    • Assess the quality of the machine translation: check for errors in syntax and style, mistranslations, omissions and structural issues. Make sure that the translated text flows naturally, the sentence structures are grammatically correct and that you review overall readability.
    • Ensure consistency: make use of existing tools, technology and techniques to maintain consistent terminology and phrasing and verify key terms are translated uniformly to provide a cohesive final translation.
    • Adapt for cultural relevance: go beyond literal translation, recognise idiomatic expressions, cultural references and adapt them appropriately so that the content feels natural and connects with the target audience.
    • Conduct ongoing evaluation of MTPE performance: collect feedback from stakeholders and users of the translated content to drive continuous improvement.

     

    Partner with an expert in machine post-editing

    At TLF, we combine a team of expert mother-tongue translators with specialist Project Managers. All our linguists have a minimum of 5 years of professional experience, hold a Diploma, BA or MA in translation and are professional members of a recognised translation body. We provide a smooth and straightforward, end-to-end post-editing service to ensure your projects are completed on time, within budget and to the highest possible standard. This has earned us a high client satisfaction rating for our post-editing projects.

    Talk to the TLF team to find out how our expert human translators can help you with your next post-editing project.

    Specialist B2B Translation Agency – The Language Factory