We all have our favourite things about Christmas. Sweet mince pies. Dressing everything up in tinsel. Oh, and of course, those terrible festive films to get you in the Christmas mood. So, we here at Verve Search started wondering: what are the most popular Christmas films out there after all?

Whether you like to settle down with a romance like The Holiday, a close-to-the-mark choice like Bad Santa, or a heart-warmer like The Snowman – debating the best Christmas films remains a strong holiday pastime. Nobody’s going to blame you if you secretly like to put on Die Hard (it technically IS a Christmas film).

To get down to the nitty-gritty of it, using data analysis we took the top 33 Christmas films from IMDB and compared how often they’re searched against their average rating to get a rundown of the ultimate list of Christmas films, including this year’s exciting new releases.

So, light a little candle, snuggle up under a blanket and crack open the Celebrations for the most popular Christmas films ever. Please, there will be no Scrooges here today…

What are the most popular Christmas films of today?

Without further ado, take a look at our ultimate Christmas film rundown. These films go as far back as the 1940s, to the latest releases from this year. They are ranked the highest-rated and most widely searched films to date and will make for a cracking binge on the sofa.

Now, there are some festive favourites that we don’t need to tell you about. Home Alone and Love Actually come first and second respectively, with an average global search volume of around 800,000 searches. That’s a lot even for the most popular choices!

Later down the list, you’ll spot family-friendly films like The Christmas Chronicles, Elf and The Snowman, just to name a few. Can’t say we’re surprised with these, with many homes most likely flicking these on for some light-hearted Christmas relief.

But some anti-Christmas classics also appear in the rankings. Coming as high as third is the old 1984 favourite, Gremlins, which some even call a horror. Following just a little behind in fifth is the highly debated Christmas action classic Die Hard with Bruce Willis.

Some interesting (and maybe even surprising) top-rankers in this category.

And some festive breakthroughs for 2024…

Every year sees a wave of new Christmas films released for the season, but they can’t all make it into the annual festive rotation. So, it’s safe to say that these 2024 releases make newsworthy features, with three choices appearing in the rankings.

If you’re shaking in your boots during horror movies, look away now because Terrifier 3 came fourth overall, with over 465,000 global searches. With its controversial reviews, the extremely gory slasher film (which had people walking out of cinemas) somehow makes for a ‘Christmas’ film, where protagonist Art the Clown transitions into quite the Santa Claus.

This one’s leading because it’s made so many waves in searches online for its bone-chilling scenes and gory details. So, even though it’s a total horror, it’s still showing up as a popular Christmas choice. Watch if you dare…

Then, Dwayne Johnson stars alongside Chris Evans for action-packed blockbuster Red One, with a budget of $250 million. Whilst some critics call it a ‘flop’ of the season, it’s got an average 6.9 rating, so it may make for an easy watch where the North Pole’s Head of Security (Johnson) has to team up with a bounty hunter (Evans) on a mission to save Christmas.

There always has to be at least one big blockbuster a year, this year it jut goes to The Rock.

And, last but not least, the most meme-able Christmas film of the season is none other than Hot Frosty. If you’ve watched it already, then you might know why it’s making such a big impact on searches.

Starring Lacey Chabert (Mean Girls) and Dustin Milligan (Schitt’s Creek), the film centres around a snowman who comes to life. Slightly hard to digest, cheesy and completely ridiculous, it’s exactly what you’d expect from a Christmas romance. You may want to wash this one down with a mulled wine due to its cheese-factor…

Which one takes the (Christmas) cake for the highest rated?

Now now, our head data elves know that just because something is highly-searched doesn’t actually make it a good film to watch. If you look closely at the rankings, there is a massive difference between what’s most searched and what’s ranked high in ratings.

Overall, audience and critic ratings end up around the 70% mark or rated at around 7.25 (out of ten) on average on both IMDB and Rotten Tomatoes for many of these Christmas films.

The highest ranked overall is none other than cult classic It’s a Wonderful Life, from as far back as 1946 and also our earliest film on the list. With an average of 8.6, maybe the 40s just did Christmas better?

Other above-average favourites include Die Hard, Klaus, Rudolph the Red-nosed Reindeer, How the Grinch Stole Christmas and The Snowman. We’ll let you decide your favourites from those choices yourselves!

On the other end of the scale with a mere 5.5 average rating is none other than the breakthrough 2024 film, Hot Frosty. Snowmen really should stay in the snow, after all.

And, this shows that whilst Christmas films can be just as cosy as they are cute, that doesn’t always mean that they’re a groundbreaking piece of cinematography – and, that’s okay. Right?

Where can you watch Christmas films on streaming platforms?

There may be nothing worse than sitting in front of the telly and not being able to find a film you want to watch on any platform. Will it be on Netflix? Amazon Prime? Hold on a second – you might even have to rent it.

Nobody wants to be doing that, so to make it easy for you we’ve rounded up where you might find these most-wanted films and on what streaming platform they’re on.

Truth is, your best bet is to get your hands on a Disney+ subscription this Christmas, with eight films being available, followed by Prime Video with six and then Netflix with four.

With that being said, you can purchase or rent all but six films on Amazon Prime Video, so you may not have to get the DVD player out after all…

To wrap up

Christmas movies are more than just entertainment – they’re a part of the whole holiday experience. From the nostalgia of The Snowman to the cult appeal of Die Hard, these choices are just as sweet as the Christmas treats.

With over 800,000 global searches for the most nostalgic Home Alone and ratings reaching averages as high as 8 out of 10, a Christmas film can create an impact. No matter where your favourite may sit in the table rankings, it’s likely that you may find yourself watching at least one of these films throughout December.

While traditional choices might dominate in popularity, newer 2024 releases like Terrifier 3 and Red One show how diverse these Christmas films have become, covering feel-good action to full-blown slasher horror. Meanwhile, Hot Frosty may not win any awards with its 5.5 rating, but it shows that these can be conversation starters (around the dinner table or just in general, that’s your choice).

And, although streaming options may not cover every title, there’s no shortage of ways to bring festive cheer into your home this year. So, happy watching! May your season be merry, bright and full of arguments about what’s the best Christmas film…

Verve Search’s most festive Christmas films

And, because the best way to spread Christmas cheer is singing loud for all to hear, we’re sharing our favourite Christmas films straight from yours truly, Verve Search.

Amber Carnegie – Creative Lead: Muppet’s Christmas Carol

“It’s got to be Muppet’s Christmas Carol. Not only is it the only retelling of A Christmas Carol to quote as close to Dickens as possible but the incredible soundtrack and the idea that Micheal Cain is running around with all those puppets tickles me. Also, the ghost of Christmas present is literally the epitome of Christmas!”

Tonje Odegard – Outreach Director: Love Actually

“Mine has to be Love Actually as I’ve been watching it every Christmas with my family since it came out in 2003, and Christmas can’t kick off without a little cry over Emma Thomson holding back her tears to the soundtrack of Joni Mitchell. After my partner came on the scene, he also learnt to love it and we now watch it together, quoting almost every line off by heart (“8 is a lot of legs, David”). It’s so British and funny and cute and annoying and I love it, love it, love it!”

Ben McNeil – Outreach Specialist: Home Alone

“Home Alone is mine, for the same reason that I’ve been watching it every year since I was very young. It takes me back in time to my childhood and makes me feel very nostalgic. Not to mention the countless hilarious moments. The vibe, atmosphere and music of the film never fails to make me feel Christmassy!”

Danae Stavros – Outreach Executive: The Holiday

“Mine is The Holiday. I’ve been watching it pretty much every year since I was a kid. It’s really funny but emotional at the same time. Hot characters are a bonus, and I like that it’s not overly focused on Xmas, but just enough to get you in the spirit.”

Giovanna Castaneda – Outreach Executive: Home Alone 2

“Home Alone 2 (when he’s lost in New York). I’ve been watching it since I was a child with my cousins, and we even played as if we were in the film! It wouldn’t be Christmas for me if I didn’t watch it. No matter how many times I’ve seen it, it always cracks me up.”

Methodology and Sources

For our ‘Christmas films’ analysis, we picked out the most popular Christmas films on IMDB, searching for those that had over 100k reviews including new releases from this year. IMDB average scores were then compared to Rotten Tomatoes critics and audience scores to create an average rating.

We then checked where the films were available to stream or purchase digitally. The streaming services considered were within the UK libraries on Netflix, Amazon Prime Video and Disney+, as well as purchase options on Amazon Prime Video.

To consider Global Search Volume (GSV), these films were searched through Ahrefs keyword analysis to determine which were most popular. GSV shows how many times per month, on average, people search for the target keyword across all countries in the Ahrefs database.

Data accurate as of 2nd December 2024.

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Around two-thirds of the UK population only speak English, and while many say they don’t feel the need to learn another language, multilingual skills can help with a mass of learning and communication skills. The truth is, there are a lot more similar languages than we might initially realise. 

Here at Verve Search, working with a multi-national and multi-lingual team, we know these benefits first-hand. Bringing a huge range of viewpoints when brainstorming concepts for clients – from the most lucrative foreign languages to Spain’s most beautiful road trips – producing campaigns about culture, languages, and linguistics comes naturally.

So, to show off the need for bilingualism and its benefits, we’ve undertaken an analysis into which languages are the closest to English (and hence make them the easiest to learn, too).

Investigating spelling, pronunciation and even using some maths, we can reveal the best languages to start your learning journey with below…

Key findings

In this study, we analysed which languages are closest to English by measuring the similarity of selected language features. The process included a range of natural language processing (NLP) methods to decipher this. 

We found:

• Scandinavian languages (Norwegian, Danish, Swedish) are the most similar languages to English, topping the board with their pronunciation and spelling.
• Finnish is the most different in all three categories, making it the hardest for English speakers to learn.
• Dutch is the closest in terms of phonetical sounds, whilst Turkish is the most different when spoken.
• Looking at the 1,000 most used words, ‘Radio’ has the most consistent spelling and pronunciation across all languages studied.

Methodology

There are three main elements to our data process. To summarise, we:

1. Gathered a list of the 1,000 most common words in the English language.

2. Translated each word into multiple languages using the Google Translate API.

3. Compared each translated word to its English equivalent to measure similarity.

Things to remember:

• We analysed the most widely spoken languages in Europe which use the Latin alphabet, and if a language has some additional characters, these were still included.
• Non-Latin alphabets are not compatible with this type of analysis. Languages such as Greek and Ukrainian have also been removed as they use the Greek and Cyrillic alphabets, respectively.
• Stopwords (e.g. ‘and’, ‘I’, ‘the’…) have been excluded.
• Disclaimer: This study analyses the similarity of individual words within each language, rather than the coherence and fluency of conversational differences. Language features around grammar (e.g. verb conjugations) and sentence structures are not considered.

How we measured the similarities of words

Now, let’s dive into the nitty-gritty of this study. We investigated two key features of words to understand their similarities and differences: their orthography and their phonetics.

First up, we have the orthographic distance between words.

“Orthography differences (spelling of words) measure how different spelling between languages is, considering alphabets, characters, and accents.”

To do this, we analysed the ‘Levenshtein distance’ between each English word in our seed list and their translated versions. Bear with us here.
 
Synonymous with edit distance, the Levenshtein distance calculates the minimum number of single-character edits (insertions, deletions, or substitutions) required to transform one string (word) into another.
 
To break it down, ‘cat’ and ‘cut’ have a distance of 1, as 1 single-character substitution is required to match each word.
 
Whereas the distance between ‘hello’ and ‘halo’ = 2, as 1 substitution and 1 deletion are required to match each word.

So, with learning languages in mind, we’ve allowed accents with the same character symbols to be considered identical, only for this orthography part of the analysis. For example, ‘Ocean’ and ‘Océan’ will have a Levenshtein distance of 0, as the accented character is considered the same as the original character. Still with us?

Lets move onto the the phonetic differences between words.

“Phonetic differences (verbal) measure the difference in pronunciation between languages. This includes individual phonemes as well as accent and tone emphasis.”

Doing this gets a little bit technical. We use a method called the Double Metaphone algorithm and a few more NLP steps. This method allows us to measure the difference between the original English word and the pronunciation in a different language by comparing the number of sounds in a word.

Firstly, we generated Double Metaphone encodings for both words (the English word and its translated counterpart, for each language) to represent how each word sounds.

Then, we measure the distance between each encoding through Levenshtein and maximum distance calculations. This distance is normalised and used as a similarity score between each word.

And breathe. That’s all for our method, but just a note on our scoring:

When interpreting our phonetic similarity scoring system, our phonetic similarity ranges from 1 to 100:

• High Scores (70-100): The words sound very similar or phonetically close.
• Mid Scores (30-70): Some phonetic characteristics are shared but are not very similar. A score of 50 indicates that the words have a balanced mix of similar and dissimilar phonetical features.
• Low Scores (1-30): The words are quite different, phonetically.

We know, it’s a little bit of a mouthful. But, it may make more sense when we put it into real data analysis. Let’s see what our results found…

Analysis

Overall language similarity: Which languages are the easiest to learn?

We found that Scandinavian languages were the most similar to English, taking all 3 top spots. Norwegian came in first, followed by Danish and Swedish.

English speakers should be able to pick up these languages the easiest, due to their high rate of similar spellings and pronunciations that English speakers are used to.

Wondering why languages from this region register as the most similar?  It goes back to the Vikings!

The Norwegian Viking invasions and settlement in England led to a significant Old Norse influence on Old English, introducing many words and impacting grammar. You’ll see this from words like ‘muck’, ‘skull’, ‘knife’ and ‘die’. Looks like they were having a particularly malicious time during this period…

However, whilst these Scandinavian languages topped the table, another Nordic language actually ranked last: Finnish.

This language differs primarily because it belongs to the Finno-Ugric language family, distinct from the Indo-European family that includes English and most other European languages. To put it simply, Finnish has fundamentally different roots.

Orthography similarity (written): Which languages have the closest written vocabulary to English?

In line with the overall index, Scandinavian languages take the top places for their written similarities too. In fact, Scandinavian dialects took the top four places for this ranking.

With an average Levenshtein distance of 3.85, that means Norwegian words are the closest to their English counterparts – less than four letters different on average. The next two languages here are Danish (3.90) and Swedish (3.94).

This time, written Finnish (once again) as well as Polish take the crown for being the furthest away from English, with a whopping average Levenshtein distance of 5.73 and 5.64 respectively. This means the average word in both languages requires 5.7 single-character edits to match its English translation.

Anyone who does speak Polish will know its vocabulary is largely distinct from English, with far fewer cognates. Although Polish has borrowed some terms from Latin, German, and other languages, its core vocabulary doesn’t align with that seen in English, making it a lot more difficult if you’re trying to learn.

Phonetic similarity (verbal): Which languages sound the closest to English?

Phonetically speaking, we measured Dutch as the closest language to English with an average phonetical similarity score of 48.2 out of 100. Where Old English and Old Dutch were both West Germanic languages, their evolution from these common roots means they retain many phonetic similarities.

On the other side of the table, you’ll find Finnish last once again – but this time followed closely by Turkish, which only scores an average of 21.3 and 23 out of 100, respectively.

What makes Turkish so different to English? That’s down to their sets of phonemes and phonological rules. For example, Turkish has vowel harmony in consideration, where vowels within a word harmonise to be either front or back vowels – a feature that’s not present in English.

 

Which words are the most similar across all studied languages?

Of the 1,000 English words analysed across 13 languages, the top three words with the most consistency in spelling and pronunciation are ‘Radio’, ‘Atom’ and ‘Dollar’.

‘Radio’ comes top with the same spelling across all languages studied, except in Turkish (‘Radyo’). The invention of the radio occurred in the late 19^th century in 1894, a time when technological advancements and global communication were becoming more interconnected. After this, the term ‘radio’ was adopted quickly around the world to describe this new technology making it a lot easier to pick up across languages.

‘Atom’ takes second place, coming from the Greek word ‘atomos’ which means ‘indivisible’. It was adopted into scientific vocabulary in the 19^th century, and with science being a global discipline, the term was retained in its original form across many languages.

‘Dollar’ rounds up the top three. Its consistency across languages is due to its historical origins in the European ‘thaler’, its widespread use in global trade and finance, and the influence of the U.S. dollar as a primary reserve currency.

Conclusion

Our Echoes of English analysis found that Scandinavian languages – particularly Norwegian, Danish, and Swedish – are the most accessible for English speakers to learn due to their high degree of similarity in both vocabulary and pronunciation.

These insights offer guidance for bilingual-curious English speakers to understand which languages will be the easiest to pick up, on an objective scale. This study also emphasises the importance of considering orthographic and phonetic aspects when evaluating language learning difficulty, aiding learners, language learning platforms, and language teachers.

Whilst Scandinavian tongues topped the tables, languages like Finnish and Turkish present the greatest challenges due to their significant linguistic differences in both spelling and pronunciation.

When analysing the 1,000 most common English words with both Levenshtein distance for orthography and Double Metaphone encoding for phonetics, this study offers a robust, comparative analysis of language similarity, particularly for the words ‘Radio’, ‘Atom’ and ‘Dollar’.

This underscores and reveals the historical and linguistic connections that facilitate easier language learning, such as the impact of Old Norse on English and the shared Germanic roots of English and Dutch.

Glossary

Accents: Difference in pronunciation specific to regions or groups within a language, often marked by different intonation and sound patterns.

Cognates: Words in different languages that have a common etymological origin and similar meanings.

Double Metaphone: An algorithm used in natural language processing to encode words by their phonetic pronunciation. Helpful in comparing how words sound across different languages.

Language Similarity Score: A composite measure of how similar a language is to English, based on both orthographic and phonetic analyses.

Latin Alphabet: The writing system originally used by the Romans, which is the basis for the alphabet used in English and many other languages.

Levenshtein Distance: A measure of the minimum number of single-character edits (insertions, deletions, or substitutions) required to change one word into another. Used to assess orthographic similarity between words.

Natural Language Processing (NLP): A field of artificial intelligence focused on the interaction between computers and human (natural) languages, involving the analysis and synthesis of language data.

Old English: The earliest form of the English language, spoken in England from roughly the 5th to the 11th century.

Old Norse: The North Germanic language spoken by the inhabitants of Scandinavia during the Viking Age, which influenced the development of Old English.

Orthography: The conventional spelling system of a language, including alphabet, characters, and accents.

Phonemes: The smallest units of sound in a language that can distinguish words from each other.

Phonetic Similarity: The degree to which words sound alike when pronounced, analysed using the Double Metaphone algorithm.

Similarity Index Score: A composite measure of how similar a language is to English, based on both orthographic and phonetic analyses.

Stopwords: Commonly used words (e.g., ‘and’, ‘the’, ‘I’) that are often filtered out in language processing tasks because they carry less meaningful content.

Xenoglossophobia: The fear of learning or using foreign languages.

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Verve Search provides international targeting for campaigns across the globe. Interested in our content marketing, outreach and digital PR services? Get in touch. 

Producing content built with AI shows that the help of artificial intelligence can open up plenty of new avenues for newsworthy storytelling.

As we’ve seen over the last few years, AI can assist content creators with a number of methodologies, including facial recognition, image generation, voice recordings and even sarcastic chatbots.

With the rise of ChatGPT (if you haven’t used it yet, what have you been doing?), we could even go as far as to say that AI has scared some of us content creators into feeling like jobs are at risk.

Luckily for now, AI hasn’t completely taken over – just yet.

With a report stating that 3 in 4 marketers are using AI for content creation, AI content is certainly on the rise with blogs, publishers and brands seeking out these tools to boost their efficiency and output. Whilst the tools are handy, it can be difficult for consumers to sift out the AI from the authentic. This, however, isn’t necessarily a bad thing.  

Looking at examples of content built with AI, there are a mass of marketing campaigns that have gone on to earn linked coverage from news publishers in various sectors.

1. How bad is your streaming music? by pudding.cool

This project is more about posing as artificial intelligence to roast a topic that many people care enough about to share: personal music taste.

Spotify’s marketing success from their ‘Wrapped’ feature has become an annual event on social media — earning over 1.2 million tweets in a single month, and leading to huge increases in downloads of the app (plus many many more brands trying to replicate it).

The Pudding’s subversion of what makes Spotify Wrapped so popular was a genius way to appeal to the cynical side of music fandom.

Their “faux AI” tool gives the impression that a sophisticated AI bot is judging your prized personal music taste in real time, before returning sharable results that are partially tailored to the user.

well, the "judge my spotify" AI is modeling human behavior pretty accurately pic.twitter.com/Z923YCTO24

— Al Shipley (@alshipley) December 23, 2020

Since launching in late 2020, it has been picked up by more than 1,300 linking root domains. 

More than 1 in 5 of the headlines mention AI or artificial intelligence, suggesting that the AI’s participation in the experience is a key selling point in the story, as well as helping to make the project possible in the first place.

2. Having a pet does make you happier, if selfies are anything to go by by Verve Search

AI image recognition technology has the potential to reveal insights on a scale that the human eye wouldn’t be able to achieve. Truth is, content built with AI doesn’t always have to be copy-based.

Using Microsoft Azure in a case study, we wanted to see whether the many selfies that exist of pet owners and their pets show a happier image than a standard image of someone without a pet.

By comparing an anonymous sample of tens of thousands of pet owner selfies to standard selfies of people, we could compare the average level of emotions displayed in either category of picture.

Combining this AI tool with geotagged image data allowed us to reveal insights related to pet owners on a more international scale.

In other cases, we were also able to use this same process to measure the happiness of the average Instagram #selfie taker and the average #newhomeowner stood outside their front door and flashing their keys.

This campaign by Neomam studios for HouseFresh also used the same tool to identify the presence and strength of smiles in order to rank the happiness of locations in the USA.

3. Are humans better than artificial intelligence at detecting fake imagery? by ID R&D

Facial recognition technology carries plenty of controversy with it, including issues around misidentification, general privacy concerns, and who it’s being targeted at.

This research comes from a company that specialises in biometric authentication software with what is likely to be an attempt at downplaying some public fears over their technology.

While the statistics back up what they would hope to find — that AI isn’t fooled by spoof photos compared to the 30% of humans who do struggle to identify fakes — this story highlights an appetite that journalists have for exploring where humans and AI clash or collaborate in their capabilities around performing certain tasks.

4. Which U.S. sports teams have the biggest ‘fair–weather’ followings? by Verve Search

Sentiment analysis tools can help us to draw insights around attitudes and emotions from large volumes of (usually) text-based data.

At Verve Search, one of our favourite use cases is to analyse the emotions behind different topics that are being talked about within various corners of social media.

In this example, we separated thousands of comments on US sports team’s official Facebook fan pages after wins and after losses to see which fan bases are more likely to remain supportive when the good times go bad and vice versa — also known as fair-weather fandom.

Initially, we would have loved to measure this on metrics such as fluctuating ticket sales or stadium attendances over a longer period of seasons. 

But with that type of data mostly inaccessible and stadium attendance figures often debated for their accuracy, we found online fandom to be a good proxy with the help of SentiStrength, which could measure individual comments on a scale of positivity to negativity.

Other newsworthy examples of this type of analysis include when we found out which household chores cause the most stress or which elements of driving cause American motorists to complain the most.

5. Males are represented four times more than females in literature by The USC Viterbi School of Engineering

This is a great example of content built with AI using machine learning to continue building on a subject of research from previous years.

An analysis of 3,000 English-language books by the USC Viterbi School of Engineering used NLP’s (Natural Language Processing) ability to detect the prevalence of pronouns, and thus how often men and women are represented in literature.

With this type of AI able to process vast quantities of text-based data and return such results, there is clear potential here for building on this method in other forms of media and entertainment where gender representation remains an issue.

6. What emotions do leaders speak with in public? by Verve Search

Public speaking is usually a prerequisite of being one the most powerful people in business or politics. 

So for this campaign we applied AI voice recognition software built on deep learning techniques to judge the emotional profile of famous leaders’ speaking styles.

Pulling together a large seed list of audio files from the public speeches of politicians and famous entrepreneurs, we could look at how certain emotions are more prevalent in certain individuals, political parties and genders of speaker.

Understanding what emotions are being portrayed within a person’s voice would normally have to be studied individually. 

With AI-driven voice recognition, you can analyse large amounts of voiced audio files and retrieve results that are compared against the average emotional levels that the software is trained on. Or you can compare the relative emotional levels from your own dataset (in this case, the average leader) to see which voices rank highest and lowest vs those average scores.

7. Can you guess the famous Christmas movie scene from this AI mock-up? by Neomam Studios

As already noted, artificial intelligence is often talked about as something that clashes with humans — our judgement, our capabilities, or our jobs. 

And although this content is built on AI-generated images, an essential aspect of its appeal requires the input of its audiences to guess what creation the AI tool has conjured up.

For this campaign that leant on a TikTok trend, each image is a famous scene from a Christmas movie that was mocked up in different styles by the app Wombo.

Thanks to this thread, where I found the campaign, you can also see content built with AI to help with other areas of the creative process:

Recently I've been playing around with AI image generation tools and I've realised there's SO many ways we can use them in digital PR

Below I've pulled together a list of 4 ways of how you can use AI image generation in your everyday 👇

— iona 🦎 (@IonaJTownsley) July 15, 2022

There’s a Buzzfeed quiz for countless trends and topics. So, it’s not surprising to see that they also had a stab at the ‘audience vs AI guessing’ quiz format in July 2022, which you can try here.

8. Supercars from a dystopian future by Screaming Frog

AI image generation tools, such as DALL-E and Midjourney can capture our imagination in just a few words and visualise a detailed version of our thoughts much quicker than we would be capable of creating in the same format.

In this content example, the AI also had to capture the imagination of the journalist to whom the content was outreached to.

In our experience, motoring journalists who report on visual content are often an exception. They are used to dealing in data, reviews, previews, and shiny photography of even shinier vehicles. 

Thanks to the creative angle used here by SEO Agency Screaming Frog, the supercars from a dystopian future is a fictional story that still managed to cut through to a sector that would normally be more concerned with stories related to cars that you can actually drive.

9. AI-generated travel posters of destinations by Screaming Frog

According to OpenAI, DALL-E is generating over 2 million images a day. 

While the volume of AI-generated imagery already seems to be saturating the internet, the strategy of defining these image outputs to link them together under one newsworthy theme could still be in its infancy.

These examples of AI-generated imagery, also from the team at Screaming Frog, were fed by the names of countries and their travel slogans to see what Midjourney returned.

The posters are visually beautiful. However, when covering the story, the journalist seems particularly intrigued by what the AI — with no physical travel experience to rely on — chooses to prioritise in its interpretation of an entire country:

“Until you’ve seen a place for yourself, it’s a bit of an abstract idea, so why not ask Artificial Intelligence to generate your travel poster?… Like most travel posters, Midjourney has evoked a fairly sketchy sense of place, sometimes punctuated by notable landmarks or natural features.”

hyperallergic.com (2022)

10. AI reimagines famous horror film posters by Evoluted

Many horror movies can be recognised by their iconic movie posters or from the faces of their terrifying villains.

The speed of AI image generation allows for trialling out different ideas for visual content. And any examples which appear to make the grade with some design touch-ups can also be targeted to a specific, short-term event in the calendar, such as Halloween.

This example by Digital PR Agency Evoluted took some of the most famous horror films of all time to see what even more terrifying versions of their posters could be reimagined by the AI app Wonder.

Check out this Twitter thread for a breakdown of the posters and more information on how they were created:

What if AI was behind our favourite Halloween classics? Using keywords from classic horror plots @vicki_collins and @laurarowleyx used AI to reimagine horror posters partnering with our design guru @willbarron to bring these to life in the style of the original posters 🧵

— Evoluted | Certified B Corp™ (@evolutednm) October 26, 2022

For more AI-generated movie poster goodness (and weirdness), take a look at this series of posters created by artist Vincenzi in his project ROBOMOJI.

Using a similar method as the Evoluted example, Apartment Therapy tells us that the artist inputted “a series of prompts and descriptions about a film’s visuals, titles, and premise into the AI software.”

As noted, the artist didn’t set out to earn linked coverage with his project. They are using it to ask important questions around what role AI will play in the art world going forward.

So, should we be creating content built with AI?

While artists and industries are rightly questioning what the adoption of these new technologies means for the future of creatives, some, like Manas Bhatia, are already acknowledging the part AI can play in quickly helping to visualise early concepts before an artist refines them with their expertise.

Back in 2022, we saw a campaign from Samsung earn widespread coverage after they enlisted the help of a digital designer to reinterpret famous artworks, according to the issues Gen-Z are most concerned about in 2022. 

Relying on insights from a survey to inform the creative direction that an artist took provided a much more human and, therefore, newsworthy angle to this ‘reimagined’ content than what the artificial mind of a tool such as DALL-E would provide.

The extent to which you use AI and its different domains as part of your creative process will vary from one campaign to another. Some ideas will see content built with AI take the role of prototype designer, others will do much of the data processing to then allow your team to find the stories that matter within the data.

On the whole, it would be a mistake to think that the inclusion of AI alone will sell in a story to the press as newsworthy.

Without a defined creative concept to work with, these examples of AI are tools waiting to process whatever we feed them. As part of our role in creating newsworthy content out of AI, we should at the very least be setting the AI’s constraints, ensuring the inputs and outputs make sense, and closely monitoring what the overall direction is of the story that we’re trying to tell.

Further reading:

1. Deep Dive: AI Image Generator DALL-E Is Now Open To All — Why Should PRs and Marketers Care? by Rich Leigh [1]
2. The future of content creation with AI is closer than you might think by David Cohn [2]
3. The lawsuit that could rewrite the rules of AI copyright by James Vincent [3]
4. Messing around with AI and content concepts by Alex Cassidy [4]

Interested in content marketing and digital PR services? Get in touch with us.

We analysed more than 500,000 tweets to reveal where Christmas shoppers are having the most stressful experiences.

As the 25th December draws closer, a trip to the high street is likely to become busier and more stressful with each passing day.

Even during the pandemic, a survey by Klarna from December 2020 revealed that 79 percent of Brits left their gift shopping until the last minute and 64 percent said they were still doing their shopping in-store rather than online. These conditions can easily make for a stressful experience when buying gifts for our friends, family and colleagues.

Can Twitter tell us whether some places are more stressful than others for Christmas shopping?

At Verve Search, we often analyse live tweets and historical Twitter activity to gain insights on certain topics from around the world.

For this article we have poured through more than 500,000 tweets to find those that mention ‘Christmas shopping’ and analysed the content of those tweets through a sentiment analysis tool called TensiStength.

This academic tool, developed by Mike Thelwall at the University of Wolverhampton, measures the stress levels of tweets on a scale of -5 (very highly stressed) to 0 (neutral).

We have used this method here to indicate which major cities in the United Kingdom and United States are seeing the most stressful tweets from Christmas shoppers and which activities and keywords within tweets about Christmas shopping are most likely to occur in a stressful tweet.

The most and least stressful cities for Christmas shopping in the UK

Although the port city of Plymouth has plenty of well-known shopping options to choose from, including Drake Circus, Royal William Yard, and Plymouth Market & West End, it is here where shoppers are most likely to encounter a stressful time while buying gifts at Christmas. Nearly one third of tweets (32.5%) related to Christmas shopping from people in the city measured as stressed in our analysis.

 

At the opposite end of the stress scale, shoppers in the Welsh city of Swansea have the least stressful experiences while xmas gift buying, with just 15% of tweets measuring as stressed in that location.

Which London Borough is the most stressful for Christmas shopping?

The London Assembly estimates more than 500,000 people walk through Oxford Street every day. And that’s just one of the UK capital’s outlets for shoppers among the many high streets, markets and shopping centres that exist there. With so many people concentrated in popular shopping areas, increased queuing times, higher competition for coveted items and busier transport links are all likely to occur, and be potential factors in raising a shopper’s stress levels.

According to our analysis of local London tweets, the boroughs of Barnet (30.3%), Hillingdon (28.5%), and Merton (28.4%) see shoppers most likely to be stressed out according to the percentage of stressed tweets in those locations.

While being the highest ranked boroughs in London, this still represents a minority of shoppers, and could be for a number of reasons. We have highlighted some of the UK and US’s most common reasons to be stressed out about Christmas shopping further down this article.

Tower Hamlets shoppers are the least stressed at Christmas time, with just 16.7% of shoppers tweeting with stressed language about their experience. Shoppers in Kingston-upon-Thames (19.7%) and Hounslow (21%) also had some of the least stressful gift-buying experiences at the festive time of year.

If you’d like to pay a visit to any of boroughs listed here and support their many excellent local businesses at Christmas, you can usually visit the local borough’s website for a breakdown of what their local shops have to offer during the festive period and beyond.

The most and least stressful cities for Christmas shopping in the USA

In America, a trip to the shopping centres of Long Beach, California are most likely to wind up as a stressful experience for people. This is based on 32.5% of shoppers tweeting about their Christmas gift buying with levels of moderate to very high stress detected in their choices of language.

However, if you are a Long Beach local or visitor, and want to support the local stores, reviewers on Yelp rate the Long Beach Exchange, Shoreline Village, and the LBX Exchange as some of the best shopping centres.

The least stressful cities to shop in are San Antonio, Texas with 6.6% of tweeters have a stressful Christmas shopping experience, followed by San Diego (7.1%) and San Jose (8%), both situated in the state of California.

Which topics and activities are most associated with a stressful tweet by Christmas shoppers?

Some of the Christmas shopping-related tweets in our analysis mentioned specific phrases and key words related to their experience. From our analysis, we found that tweets that talked about ‘expensive gifts’ and ‘Christmas shopping’ were most likely to be stressed — equivalent to 75% of tweets — compared to other potential indicators of shopping stress, such as face masks, the weather, and money problems.

Methodology

We scraped more than 500,000 tweets in the 40 most populated cities in the UK and 50 most populated cities in the USA, and every London borough over two weeks between late November and early December.

With these tweets we analysed those which mentioned ‘Christmas shopping’ (equivalent to more than 62,000 tweets) with a tool called TensiStrength. This gave us a score for each tweet on a scale of 5 (very highly stressed) to 0 (neutral). Stress levels are detected according to the type of words, phrases and punctuation used. 

A stressed tweet was categorised as any tweet with a score of 2, 3, 4, or 5.

To calculate what makes Christmas shopping stressful, we analysed the final sample of Christmas shopping tweets for mentions of each key word or phrase. Each tweet that contained target key words and phrases was measured according to what percentage of them measure as stressed.

Disclaimer:

Opinions on Twitter don’t tell the full story about visiting a place in real life. While some of the locations mentioned here may coincide with a ‘stressful’ experience from Twitter users, that shouldn’t put people off shopping there (in-store or online). 

• You can find out more information about where to shop with local businesses on local council websites, via: Local.gov.uk
• You can shop independent and local at: locallyuk.com
• How to support small and local businesses in your community [1]

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Figma is evolving at an incredible rate. With a recent edition of FigJam and updates such as Cursor Chat and Audio, editors and viewers can collaborate even more effectively, saving time and resources.

One of the best things about Figma is the ease with which you can install all sorts of incredibly helpful plugins. If you’re new to Figma, it can be hard to know where to start – so here’s my guide to the best Figma plugins of 2021.

Master

Are you wanting to attach objects to an existing component or merge two main components? No problem. This plugin can help create, clone, and move components without losing overrides. While it might take some time to master this plugin, it’s absolutely worth it. Find out more about Master here.

Convertify Figma to Sketch/XD

In a previous blog, I touched on the differences between Figma and Adobe XD. For those designers that still have to toggle their design work between the two platforms, you might find the Convertify Figma to Sketch/XD plugin very useful. It easily converts and exports your design files from Figma to Sketch, Adobe XD, or After Effects with one click.

Adee Comprehensive Accessibility Tool

Adee is the plugin for you if you need to test your design out for accessibility. Adee is a powerful tool that offers a wide range of functionalities, including the game-changing colour-blind simulator. This feature lets designers select their design frames and preview them in eight colour blind modes within the Figma app.

Find / Focus

Alright, we’ve all been there – the larger the project, the harder it is to find that one layer. The Find / Focus plugin solves the difficulty of manually searching through endless layers in your document with its find, select, and zoom feature. Just type the layer name into the search window and refine your search with additional regex or case sensitive options.

Status Annotations

For those who use Figma’s free Starter Plan or like to keep all their design versions on one page, Status Annotations could be a helpful plugin addition. Although the status labels are quite small, this plugin does the job. It indicates the status of the design process for any selected element – a collaboration feature we needed!

Font Scale

Fonts can be difficult at the best of times, especially for those who are just starting out in design. Font Scale helps designers achieve harmony and consistency in a typographical hierarchy. With several scale factor options to choose from, Font Scale generates font size previews.

Figma Chat

As previously mentioned, Cursor Chat does a great job as an instant messenger within Figma; it’s innovative and super helpful for collaboration work. However, if you are looking for something a bit more old school, the Figma Chat plugin is a great option.

This plugin lets you communicate with other people inside the Figma file. You can also select a frame or an element and attach it to your message so that the recipient can find that element quickly.

Final thoughts

As we’ve discussed in a previous blog post, the design team at Verve Search uses Figma because of the sense of community that the platform encourages with features that allow for enhanced collaboration between creatives. If you’re new to UX and UI design, check out our selected plugins to see how they can work for your workflow and improve the collaboration on your team.

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I was given the opportunity to attend the inaugural Outlier 2021 conference hosted by the Data Visualization Society. It featured 41 inspirational talks given by people who work across different industries, each with unique and varying levels of experience in their data visualisation specialisms.

There were so many talks to choose from, but I’ve narrowed down five that will help to reframe how you think about the process of creating impactful data visuals.

1. How do we translate cultural experiences into data stories?

Hosted by Isabella Chua & Mick Yang (Kontinentalist)

The talented team at Kontinentalist create engaging data stories that unpack cultural experiences to gain a better understanding of cultural trends.

In their talk, I learnt the following tips to create a compelling data story that translates other cultures:

• Find an angle that is proudly niche
  
  If you are translating your own cultural experience, do it with pride and communicate it with an urgency that suggests if you don’t tell your story about your experiences then other people won’t be able to either.
  
  Explore a particular angle of interest in-depth, rather than being too wide-ranging in exploring a number of angles at surface level.
  
  This can be something as simple as introducing one lesser-known artefact or phenomenon from your culture and communicating it in a way that educates and informs a wider audience from outside of your culture.

• Unpack diversity within your angles to explain how certain phenomena are experienced within that culture.
  
  This can mean helping your audience to understand the ways in which cultural phenomena interact with the lives of different groups in that culture (e.g. What’s the big deal about chilli in Asia?).
  
  In this example, chillis provided an excellent window for exploring Asian cuisines and the influence that chillis have upon many dishes.
  
  The author began his analysis by asking ‘was spicy food popular in Asia?’. But the yes-no nature of the question provided added complications to finding a definitive answer to something not comprehensively documented, so he refined his analysis to explore ‘what ways spiciness – in particular, chillis – were experienced in Asia’, which was more open-ended and allowed for unpacking the answers in a less binary fashion.

• Test conventional wisdom to dispel common myths (e.g. All the shades of Lee Hsien Loong).
  
  It’s a common myth that the Singaporean prime minister Lee Hsien Loong mostly wears pink shirts. After collecting data on all the shirt colours he’d worn during PM speeches it was revealed that his most commonly worn colour was actually white.

• Quantify the intangible
  
  Some cultural phenomena might have a concept that is quantifiable (e.g. the popularity of different noodle brands).
  
  But even if there isn’t an obvious quantifiable metric, you can translate the qualitative stuff by providing a rich visual experience via maps, audio or illustrations to convey the theme, atmosphere and cultural significance of your story’s topic.
  
  In the below example, colours were used to convey the different dimensions of flavour used in Asian cuisine. Additionally a packed circle chart was used to visualise common ingredients in chilli dishes with chords connecting circled ingredients that go well together.

• Balance accuracy and understanding to ensure that the data is well presented and easy to understand.
  
  The above visualisation of ‘ingredients that go with chilli’ is actually a condensed version of more than 100 different bubbles that had to be indexed on a scale of between 1 to 9 flavours (such as ‘sweet and sour’).
  
  While this is a less accurate representation of the very distinct flavours that exist within these many ingredient combinations, the authors felt this struck the right balance between beauty and simplicity. They were able to provide more detail through the illustrations and text boxes that more curious readers could explore.

• Find a common ground
  
  It can be easy to over-explain when trying to tell a story about one culture to an audience outside of that culture.
  
  Here, they recommend anchoring the angle of the cultural experience that you’re trying to analyse to a more universal sentiment.
  
  In the talk, they used an example of relating the cultural tradition of new year fortune telling to people’s universal anxiety about the future and our well wishes for loved ones, or of the popularity of instant noodles in Asia to every culture’s respective love for certain comfort foods.

2. 3D Geo DataViz: From Insight to Data-Art

Hosted by Craig Taylor (Senior Data Visualisation Design Manager, Ito World)

Craig and his team at Ito World create narrative-driven and cinematic-looking 3D visualisations.

Craig’s talk focused on how he and his team create insight-driven visualisations that reveal how the systems we interact with impact our lives. In his talk, he explained that producing this type of visualisation requires that you:

• Include granular data, since it yields more interesting results. For example, for Ito World’s project Transit In Motion, the dataset for New York City included 14.8 million locations recorded per day, 4,488 unique bus trips, and 2GB of CSV files.

• Focus on the patterns that your data is creating over time. For Transit in Emotion, this involved analysing the volume of transit usage over the period of one month.

• Make your visualisation’s design abstract to highlight the rhythm of your data over time. In the past, Craig has used a variety of spheres, cuboids, and meshes to portray what city-wide transit in motion looks like. 

3. DataViz, the Unempathetic Art

Hosted by Mushon Zer Aviv

Mushon is a Tel Aviv based designer, researcher, educator, and media activist. His talk highlighted how data viz can lack empathy, and takes inspiration from the following quote:

To ensure that your work is empathetic, Mushin says you must be aware of:

• Dark data viz, which risks tone-deafness and minimising important topics.
  
  In 2015, Mathew Lucas produced a series of infographics showing the impact of the atomic bombing in Hiroshima. Although the graphics were visually pleasing, this data viz also sparked debate, with some questioning how design should be used to aestheticise a horrific event.

• 

• 

• How an appeal to empathy can be misleading
  
  Mushon cites Professor of Psychology Paul Bloom who says empathy often shines a spotlight on the individual and can be biased towards those who look like us. We find it easier to empathise with individuals, not with the masses.
  
  He also references a study from Paul Slovic in the talk, which further illustrates this idea with what he calls ‘statistical numbing’ whereby audiences seem to empathise more with individuals than with larger groups.
  
  In Slovic’s research he found that charity donations in response to descriptions about identifiable individuals earned more than double the donation value in response to descriptions about statistical lives (i.e. groups of individuals that weren’t personally identifiable). Sadly, the value of donations even decreased when statistics were presented alongside individual descriptions in the story.

• Affective empathy vs cognitive empathy
  
  According to Simon Baron-Cohen, affective empathy, which is rooted in emotion, means that you’re able to feel the same emotion or feel your own distress in response to another’s pain.
  
  Cognitive empathy, which is more rational, means that you’re able to understand someone’s perspective or imagine what it’s like in another person’s shoes.
  
  Muson relates these two types of empathy to Daniel Kahneman’s distinction between two ways of thinking:
  
  Tier 1 thinking: thinking automatically, quickly, with little or no effort and sense of voluntary control.
  Tier 2 thinking: allocates attention to the effortful mental activities that demand it. These type of operations are often associated with the subjective experience of agency, choice and concentration.
  
  It is said that Tier 2 often contextualises the thinking of Tier 1 to inform a person’s decision-making. In visualisation, the pre-attentive attributes (below) are how we use vision to communicate between Tier 1 and Tier 2. So here Mushon asks ‘can we think of empathy as an additional pre-attentive attribute for visualisations?’ because we do not get to control or rationalise it, but it can inform our more deliberate decisions.

• How to scale compassion by appealing to both types of empathy

The above image is a powerful visualisation of gun deaths in America during a single year. It begins by illustrating the life arc of one person being cut in the middle vs how many more years they could have lived for.

Focussing on a single individual’s life being cut short appeals to the viewer’s affective empathy or tier 1 thinking, aka the more emotional response, before the impact of another 11,422 deaths are visualised in the same manner as below.

• Raising awareness is not enough
  
  Data visualisations have the power to explore and explain important stories about the world.
  
  However, it’s not enough to just say something is wrong with the world. If we have built that message well, then we should also direct that message towards the path of change and actionable insights.

4. Data points are people too

Hosted by Bronwen Robertson, Joachim Mangilima, Saja Othman, Zdeněk Hynek

Data4Change is a non-profit organisation based in London that connects social change organisations with designers, journalists, and technologists to collaboratively create data-driven solutions for some of the world’s most pressing problems. This talk focused on many of their projects which have helped to deliver change in countries around the world.

An example of this is ‘A Bride With A Doll‘, which focused on the issue of child marriage. The team designed a workshop kit and a storybook that could be read from both directions, reflecting emotional experiences, based on data insights from the community.

5. Mind Games: The psychology behind designing beautiful, effective, and impactful data viz

Hosted by Amy Alberts (Senior Director, User Research, Tableau)

This talk outlined practical guidelines which can help you predict where people look at certain parts of data viz – for example, jagged lines and bar graphs are effective at drawing the user’s attention.

Amy’s team at Tableau have previously employed eye-tracking software to discover where people were focusing, gaze plots to qualitatively and quantitatively show where the eye is fixated, heatmaps to show areas of high visual tension, and gaze opacity maps to highlight areas that people give less attention.

According to their findings, the biggest attention grabbers in data visualisation are:

• BANS (Big Ass Numbers) – Our eyes are drawn to large visual elements such as big text. Below is a gaze opacity map of a dashboard with big numbers.

• Colour ­– Visual contrast relative to other areas generates attention.

• Humans and maps – Our brains are hardwired to notice other humans, so when we see human-like figures in visualisations, we are automatically drawn to them. If maps and humans are relevant to your data, it is worth capitalising on this to draw attention.

Design with intent and be mindful of the context that you control. Use clear titles and high contrast elements, ethically making use of the psychological phenomenon known as the priming effect. This will help to ensure that your audience clearly understand the story that you are trying to tell with your data.

Final thoughts

The Outlier conference was incredibly informative and packed with so much knowledge about how to create culturally relevant, socially aware content that’s also visually impressive and effective in communicating concepts.

If you are interested in learning more, you can watch a playlist of video recordings with all of the talks from Outlier 2021.

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For this post, you’ll learn about the benefits of using mood boards to communicate ideas to clients with different types of requirements. I’ll be using real examples created by Verve Search’s designers.

But firstly…

What is a mood board?

A mood board is a type of visual presentation that consists of several design elements in one composition. It’s a way to visually communicate your imagination with the world, as well as convey a general idea or a feeling about a particular topic. 

Mood boards can be physical or digital. For example, a UI designer might find a digital version a better option for organising inspiration for a new mobile application. 

Conversely, someone like a perfumer may want to use a physical mood board to include textures and objects to convey the emotion and mood of a unique perfume scent.

The benefits of using a mood board for client work

Mood boards are a valuable step in the design process as they help establish a strong foundation to the look and feel of a project and can be used to creatively align with project stakeholders early on. 

They are a fundamental transition between an initial thought and a first draft, and help save on resources and energy when maturing ideas. 

Mood boards should be a jumping-off point for discussing, refining, and trying out ideas without commitment, while also making sure that the team and the client are on the same page as the designer.

At Verve Search, we use digital mood boards in the production process to communicate the mental model of a designer who is working on a campaign. Mood boards help transform ideas into a collage of useful visual references, and there are lots of options you can explore on what to include in your own digital mood board.

What to include in a digital mood board for a client

A mood board is a collection of elements, such as colour, typeface, UI framework, or theme, that visually unifies a set of images. You might also want to include customised design elements that will be used in the final design. 

That being said, content visualised on a mood board doesn’t necessarily have to appear in the outcome of the project; the visuals could just serve as a way to describe a feeling or aesthetic.

Below is an example of a mood board I presented to our client Paxful for the Video Game Investments campaign. As you can see, I’ve included different icon ideas, a colour palette, an example of typography, UI inspiration, imagery, and a logo. 

On your mood board, you might also want to include different textures, shapes, and interactions between elements to give the client an idea of how you visualise your project’s look and feel.

Mood boarding approach

The way you should approach mood boarding at the beginning of a project depends on the type of project it is; is it a personal project or work for a client?

Working on a client project often means there is less freedom to experiment with design concepts, as there might be some existing client requirements or style guides in place. This is true especially for clients that already have an established design vision. 

In this case, the mood boards should give a sense of the client’s taste and requirements while also exploring some potential design directions. 

Below, I’ve detailed the ways the design team at Verve Search has approached three different client requirements and included some examples of our resulting mood boards and final designs… 

1: Clients with a style guide and extensive requirements

In the first example, I will talk about clients that provide a style guide and have strict requirements when it comes to the look and feel of the final product. 

Below is an example of a mood board that was put together for Lookfantastic’s Instagram Emotions campaign. The mood board includes some imagery from existing assets belonging to the client that serve as design reference, and some elements from their style guide, such as colour and typography. The mood board also includes some inspiration for the way our findings could be visualised in a map and pie chart.

Looking at the final design below, you can see how I maintained a similar layout and colour scheme to the ones showcased in the mood board.

Working with clients that have strict design requirements and style guides in place might seem like a bit of a creative challenge, but having access to a client’s style guide is a helpful way of understanding the client themselves – especially if you are new to working with them. Overall, their style guides will contribute to better communication and a mutual understanding of what will be expected from the designs.

2. Clients with a style guide and minor requirements

For The Jargon of Jobs, our client Canva provided us with both a style guide and some minor design requirements to keep in mind. We were tasked with creating a playful feel, using Open Sans as our font choice, and selecting an accent colour from the two they had provided us.

The resulting mood board for this campaign included some style guide references, inspiration for data visualisation in the form of a map, and some examples of trending design choices that we believed would work well as a design direction for this project.

The final design included all client requirements in terms of font, colour, and mood. On our side, we added a custom-made illustration depicting confusion (which worked well with the campaign’s theme) and a trendy radiant gradient to complement the logo.

For this type of client, I’d recommend not getting too attached to a particular style or a design vision. It’s a good idea to have a few options in mind, for example a more experimental design and also a safer design option. In the case of the first design option being rejected, you can always fall back on another design option that you have at hand.

3. Clients with no style guide or specific requirements

For our client Admiral’s campaign Home Alone 2021, the client gave us complete freedom in terms of design choices. We did however have to create a layout similar to the previous Home Alone campaign, for which this campaign served as a 2021 update. 

Since the topic for this campaign was vacant homes, we thought it would be great to reflect this with visuals like architectural blueprints. Therefore, a clean feel and accents of blue can be recognised in this project’s mood board. Other mood board elements included inspiration for the navigation aspects and snippets of the previous campaign.

Home Alone 2021’s final design featured a clean layout and an aesthetically pleasing colour scheme, with a large illustration of a lonely, isolated house on the splash page that made the interface more engaging.

From personal experience, I have worked on various campaigns and they all differed in their look and feel. Each project had its own concept that needed to be projected through design.

There have been campaigns that required more effort regardless of it having or not having a client’s style guide in place. No project is the same, but this is why mood boards exist – to help creatives in starting a project in the right direction.

How do the designers at Verve Search approach the mood boarding process?

The steps outlined below refer to the design stage of the campaign creation process. This is the standard mood boarding process as followed by the design team at Verve Search and may be a helpful guide if you’re starting out on a design project. 

Step 1: Campaign kick-off

Campaign kick-off is the first meeting we have as a team when starting a new campaign. During this meeting we get briefed on the campaign’s concept and have the opportunity to ask campaign-related questions. For designers, this would usually be the time to ask about the client’s requirements and the creative team’s expectations.

Spending some time researching will help you visualise the ideas better during campaign-related meetings. This could apply to prior campaign kick-off or data handover.

Tips at this stage:

1. Understand the concept of the campaign
2. Understand the client and what they want to achieve
3. Note down relevant keywords

Step 2: Brainstorming

At this stage, the key is to write down as much relevant information as possible. Try to combine all the knowledge you’ve gathered on the project so far and start to think about what could inspire you, products to be inspired by, colours, and anything that could impact the design. 

One way to do this is to take a piece of paper and start writing down keywords. You can then categorise them into groups like style, font, or colour. This process will help to organise your thoughts and transform mere imagination into a workable concept.

Tips at this stage:

1. Create a word cloud using relevant keywords and associations
2. Note initial thoughts on the look and feel of the campaign
3. Research possible ways to visualise the data

Step 3: Initial mood boarding

The initial mood boarding process should set the mood of the campaign and define a desired emotional response. These are the emotions a viewer should feel when looking at the mood board. 

Try jotting down adjectives that define the style that needs to be achieved and organising all the images you’ve collected according to their common visual theme. It’s important to eliminate any images that look alike or unnecessary – less is more.

Tips at this stage:

1. Analyse the client’s style guide
2. Analyse the client’s website or similar platforms 
3. Search for visual references and concepts on Dribbble or sources alike
4. Explore fonts (if not provided by the client)

Step 4: Data hand-over and mood board refinement

Once the data has been handed over to the designers and the content of the campaign is clear, it’s time to make final refinements to the mood boards by adding and removing visuals where appropriate.

Tips at this stage:

1. Refine the mood board according to the campaign’s content
2. Refine the mood board according to the campaign’s data

The takeaway from all of these steps is to organise your work, even if you are just brainstorming. Doing prior research and making a note of initial ideas could really help you later in the project. You will be able to go back to the initial ideation process and understand why you made a certain design decision. This is also helpful when presenting your work to clients or your team.

Final thoughts

Mood boards are an uncomplicated way of communicating a design concept that minimises any misunderstandings that might arise from trying to describe a concept verbally.

A good starting point for any designer is research, including reading through the client’s style guide, looking for the market’s standard in colour psychology, typography, and overall design. 

Since mood boards are usually shared with non-designers, it’s important to arrange them in a way that will make sense to viewers who are new to design as well. 

Further reading

Take a look at the below resources for further mood boarding inspiration:

Dribbble

Behance

Awwwards.

Typewolf

Muzli

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