Step inside our black box.

We analyse your first-party sales data to spot those transactions that have been triggered by word-of-mouth and then make recommendations to amplify that impact in the future.

Word-of-mouth leaves a very different footprint compared to sales driven by other factors, such as advertising campaigns, press coverage or Google ad spend.

Our algorithm is trained to pick up the patterns that are unique to your brand. It’s an approach we spent 15 years developing with some of the UK’s best data scientists.

Think of it like a wildlife tracker… Yes, we love an animal analogy at Herdify. Wildlife trackers are trained to spot tiny changes – patterns – in the wilderness, such as track marks, broken twigs, changes in the grass direction. That’s exactly what our data scientists do with your data.

Once we’ve identified where word-of-mouth conversations are happening, we’ll provide you with recommendations about where your campaigns will have the biggest impact – now and in the future.

It’s an approach that leads to an immediate uplift in ad performance and sales conversion time, all thanks to the power of word-of-mouth.

We analyse your first-party sales data to spot those transactions that have been triggered by word-of-mouth. Sales driven by other marketing activity leave a very different footprint to word-of-mouth sales, and our algorithm spots the patterns that are unique to your brand.

Think of it as our secret sauce – developed by 15 years of scientific research by leading data scientists.

There are Lower Layer Super Output Areas (LSOAs) and Middle Layer Super Output Areas (MSOAs).

LSOAs are built from groups of Output Areas (clusters of postcodes) and have been automatically generated to be as consistent in population size as possible. On average, the population size is 1,500.

MSOAs are built from groups of LSOAs and are also as consistent in population size as possible. On average the population size is 7200.

The data sets are converted from a download of geography data from the Office for National Statistics (ONS).

We can work to the level of either data set, depending on the volume of your data and your strategic objectives.

The Office for National Statistics (ONS) is the UK’s largest independent producer of official statistics and the recognised national statistical institute of the UK. They class output areas as the lowest level of postcode numbers that are GDPR-compliant.

The Information Commissioner’s Office (ICO) is the UK’s independent authority setup to uphold information rights in the public interest, promoting openness by public bodies and data privacy for individuals. Our registered number is C1103520.

Yes, they do. It varies though – they may change 15-20% or sometimes as much as 60%. The targeting is all about where and when. It’s not always the right time to target, and our recommendations allow for monthly change to capture intent and influence at the right time.

It also depends on the medium, and we can be flexible with this. For example, Out Of Home activations are longer term for example, so we would look for more stable areas, whereas digital can be every month. In every case, we’ll help you activate the recommendations and find the best way to use the data.

We can slow down the frequency if required. Monthly is as fast as we go, but if this is too fast then we can adapt accordingly.

We generally advise against demographic filtering. If you think about how word-of-mouth transmits, the message isn’t always spread by the target demographic.

An example we like to share… Our CEO Tom is a Foo Fighters fan. When their last book was released, both his mother and mother-in-law saw an advert for the book and sent a message to Tom about it. Neither would be in the Foo Fighters demographic, but they played an important part in the subsequent sale.

Filtering by demographics can inhabit information flow. On a national level, we realise it’s ridiculously expensive to remove demographics, but it’s much more achievable on a local level.

There’s no fixed rule, it depends on audience size. We look at what you’re looking to spend and we prioritise the audience accordingly.

We do not model individual behaviour – we model group behaviour and network effects.

One person in a group buys something, others become aware and start to consider it – by the time a few more have purchased the rest of the group will likely purchase without much thought. This is the pattern we look for, the complication being the time and distance between each sale is different for each brand. This is essentially our USP.

Google has announced it will delay the removal of third-party cookies in Chrome until 2024. It’s the world’s most popular browser so the change will lead to a marked shift in the way that brands allocate their ad spend.

When Apple moved to allow iPhone users to decide whether or not they were tracked by apps in 2021, it made targeting new customers that much harder. Platforms such as Facebook have lost billions in advertising revenue and small businesses have had to deal with rising prices and diminishing reach.

With less access to third-party data, digital ads just aren’t as effective as they used to be.

Marketers are understandably concerned about Google’s planned changes. One survey found that 41% believe they’ll struggle to track the right data, and many predict they’ll need to increase advertising budgets by as much as 25%.

There is another way.

Herdify helps businesses optimise their first-party data to become much more targeted in their ad spend. Using an approach developed from 15 years of behavioural science modelling, our data team take a brand’s historical sales and identify where word-of-mouth is generating activity, to predict where those audiences are who are most primed to be targeted next.

Real actionable insights to turbo-charge your marketing strategy – now and in the future.