Unifying Brand Marketing and Performance Marketing with Data

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Unifying Brand Marketing and Performance Marketing with Data

The purpose of this article is to better understand the roles of brand marketing and performance marketing in relation to one another, and to unify them both in a strategic framework which can then be practically applied in real world situations across the relevant areas of marketing. These strategic considerations and practical applications are currently in use at 77Agency – Jakala, underpinning the campaign strategy foundation of clients.

In this article we will explore the following:

  • How brand marketing and performance marketing should not be measured and analysed in separate silos.
  • How some marketing theory helped develop an inaccurate dichotomy to help explain different considerations and data points.
  • Get insights into how this dichotomy is properly resolved using a new framework of improved understanding.

To understand the current status of perceived utility and methodology, we must first examine the history of the divergent models in order to better understand their respective positions today.


A history of Brand marketing and Performance marketing

The sales funnel dates back 1898, when Elias St. Elmo Lewis first developed its use for a marketing model, called the AIDA model (fig.1).



The AIDA model worked simply as an overarching model to explain the role of marketing with regard a customer’s purchase journey. The funnel shape was perfectly applicable in this instance as it rightly assumed that less people would buy a product than those who would not buy it. The simple 4-step process explained marketing should evolve in 4 key stages:

  1. To build awareness of brand and products/services
  2. To create interest in brand and products/services
  3. To develop a desire for brand and products/services
  4. To make people buy (as the action) brand and products/services.

This model is still used today, and fundamentally there is nothing wrong with it, so long as it is used in the scope in which it was designed to be. This model helps to explain a customer journey only, it does not help to explain how marketing should be employed alongside it, beyond the self-evident strategies that ads should create awareness, interest, desire and actions based on where the customer sits in the AIDA model. However, the funnel shape persisted through the decades, later adding to the inconsistencies with some modern thinking on brand and performance marketing we are now exploring.

In the late 1990s, the customer journey started to move more online. As more and more customers bought products and services from a website, these customers were then served a thank-you page after purchase, which contained 1×1 tracking pixel, which was counted as a sales conversion. The term “pixel” is still used today for the tracking code that is added to websites to measure sales success. With the increasing number of online sales “conversions” now becoming more and more evident in the sales analysis, the funnel evolved to better incorporate the new medium (fig.2):



The top of the funnel (“awareness”) remained the same; the middle of the funnel was simplified – “interest” and “desire” becoming the one phase “consideration” (interest and desire representing similar customer emotions, as different ends of the same spectrum, rather than distinctly different customer states and therefore analytically less useful); and at the bottom of the funnel, “action” became “conversion”, this being the new currency of success in online.

With the unprecedented growth of Big Tech during the late 90s and 00s, also using this terminology to reposition the sales analysis in a more digital setting (thus also benefiting themselves and underlining their input) the 100 year old sales funnel was very much imprinted in the modern marketing mind, indelibly almost as a go-to standard. Again all fine, so long as it is used to explain the user journey only, not try and demonstrate how the journey can be influenced from an outside (funnel) marketing perspective. However, with the growth of new digital marketing agencies, each trying to differentiate themselves in a quickly crowding market, the funnel was adapted again (fig.3 below) now trying to show how branding and performance marketing worked at different stages of the sales funnel, independently as a kind of handing-over-the-relay-baton moment in the customer journey.



This oversimplification, and therefore analytically less useful iteration, helped marketers to better segment their attention and effort. However it also created a divide between branding and performance, separated strategy and creative, and drove a wedge between short-term and long-term sales and marketing planning. This helped a handful of companies, those looking to appear different by picking a side; in the whole though, this was damaging to marketing strategy, having created an illusory divide between entire teams and business priorities.

To explain why this is an oversimplification of how brand marketing and performance marketing work in practice, we will now examine its different types and evaluation models.


Examples of Brand marketing and Performance marketing

Les Binet (adam&eveDDB) outlines two fundamental types of advertising as follows:

  1. Broad reach ads that people find interesting & enjoyable
  2. Targeted activation that they find relevant & useful

This very fundamental breakdown of advertising into 1. Branding and 2. Performance, help marketers to better understand the ways in which their advertising has an effect. Where the effect is directly measurable then this in turn helps to evolve a campaign strategy to create more desired outcomes. This process is repeated ad infinitum. Examples of these desired outcomes (campaign metrics) are as follows:

  • TV – Viewers, Reach, eCPM, Spont. brand awareness
  • OOH – Impressions, Reach, eCPM, Spont. brand awareness
  • Radio – Listeners, Reach, eCPM, Spont. brand awareness
  • Print – Circulation, Reach, eCPM, Spont. brand awareness
  • Search – CR, CPL, CPA, ROAS
  • Social – CR, CPL, CPA, ROAS
  • Online Video – CR, CPL, CPA, ROAS
  • Content – CR, CPL, CPA, ROAS

Historically, these channels were organised into two halves: “above the line” and “below the line”. The terms date back to 1954 and Michael John Baker, who used the distinction to segment marketing channels into two types, where “above the line” meant those channels that consisted of “broad reach ads” (as defined by Les Binet) where the target audience was historically unknowable; and “below the line” which involved “targeted activation” (Les Binet definition) where the user was known and specifically targeted. The split as it refers to the channels above is as follows: TV, OOH, Radio, Print (above the line); Search, Social, Online Video, Content (below the line). This system was useful in regard to helping marketers better understand their day-to-day marketing efforts; however, it wrongly helped to cement a divide between the two types of marketing we are exploring here – brand and performance marketing. The ATL/BTL system was also incorporated into the traditional sales funnel (fig.4) normally as follows:



The ATL/BTL distinction is still used in some marketing conversations today; however, looping back to earlier in the article, when applied to the traditional sales funnel (explaining the customer journey and the progressive buying states) the ATL/BTL distinction when applied here should only be used to explain the marketing channels as they historically relate to the customer journey, and only then in the buying cycle broadly and not from a tactical or strategic perspective.

This model, as applied to the traditional sales funnel, was fine up until the 90s, when ad spend started to shift to online, it is from this point onwards that the model became less accurate and with the advances in technology and tracking, the channels above started to shift to their online equivalents as follows:

  • TV – Viewers, Reach, eCPM, Spontaneous brand awareness
  • OOH – Reach, Impressions, Spontaneous brand awareness
  • DOOH – CPM, Location data & Beacon tracking, Geo data uplift
  • Radio – Listeners, Reach, eCPM, Spontaneous brand awareness
  • Digital Audio – CR, CPL, CPA, ROAS
  • Print – Circulation, Reach, eCPM, Spontaneous brand awareness
  • Website/app – CR, CPL, CPA, ROAS

This evolution meant that nearly all the traditional channels could be measured in the same way as the existing online channels (Search, Social, Online Video, Content) meaning that an improved methodology, or model of understanding, would now need to be employed to make this useful beyond the simple customer journey.


Targeting & Media Planning

In companies and agencies historically, media planning was divided up by specific teams based on the channel type and the different skillsets and tools required to design the best marketing plans to achieve agreed business goals. This made sense when audience measurement was not standardised across channels, different teams needed to be versed in different auditing methods, so different planning teams worked in separate silos, coming together in the final stages to deliver a complete media plan. Now, target audiences are knowable across all channels, targeting data points are more standardised and detailed targeting personas can be created and applied to the historically divergent channels. Now, it is in the data that marketing success is found. Now, it is the best data and the understanding of this data, which sees one campaign fly and another one fall. Those marketers that understand the role that data plays, across both brand and performance marketing, and those who have retooled themselves to the make the most of the increasing data touchpoints, are those who will see the most success today and tomorrow.

At 77Agency – Jakala we make sure that our data understanding is second-to-none; more than that, we have committed to constantly question our working methodology and the tools that we use to collect and segment data. We have developed proprietary tech to make better data models and see greater marketing campaign success for clients. One such example is Hexagon (fig.5).



Hexagon enables more detailed profiling of customers and prospective customers in their real-world locations. Client data can be enriched by the largest micro-territorial database of 60 million users, and potential customers can be mapped at a street level, creating hyper-targeted segments for improved campaign performance. At its core, Hexagon is a tool to improve marketing performance by enabling campaign optimisations at a minute level of detail. More than that, visualising this operation is now possible within the reporting dashboard, enabling this understanding to be shared between teams and stakeholders for continued improving performance.

This level of targeting data is now requisite for media planning. Without this increasing level of data detail, marketers are only planning at surface-level. Improved data enables a deeper level of planning; better planning and increased target audience understanding means a better campaign activation and more significant results at launch and onwards.

Brand marketing running on traditional channels should be planned using all new data touchpoints, including hyperlocal targeting made possible with Hexagon. Only when all data touchpoints are properly analysed within a comprehensive framework, cognisant of all marketing channels, is it possible to derive properly robust conclusions. Traditional marketing audience data touchpoints enhanced with overlays of richer data, including hyperlocal geo targeting, improved 3rd party data understanding through 1st party data analysis collected from newer media formats like CTV, DOOH, Digital Audio, and a test-and-learn methodology which allows for flexible planning based on the latest data and an evolving understanding of how to segment and utilise it.

Another advantage that comes from a geographical visualisation of campaign success/conversions, is one to do with attribution. Whatever your attribution model (last click, first click, linear, time decay, position-based, data-driven – definitions as per Google) all are still unable to surmount fundamental issues with campaign sales attribution as follows:

  • Cross-device customer journeys
  • Cross-browser customer journeys
  • Cookie expiration due to ITP
  • Cookie blocking, VPNs, incognito mode

Each of these tracking obstacles makes it harder to associate campaign success with the correct advertising trigger/data point, which makes campaign optimisation more challenging. By mapping campaign success at a hyper-specific geo-level however, it is knowable at individual street level, which is then optimised for accordingly. For example, a unique customer journey can traverse multiple devices and browsers before buying something, so learning about this customer can be challenging for cookie-reliant platforms. But mapping this customer’s journey physically is never cookie-reliant and learnings are then made by extrapolating other buying patterns in the same real-world locations. The result is campaign optimisation based on every possible conversion data point as normal, but then understood in its real-time, real-world setting, not reliant on cookies and further immune to loss of data-point-joining due to user privacy settings.



With increasing audience understanding and deeper knowledge of who, when and where to target, creative strategy is then the next focus for marketers. New tech in creative build and execution allow for the same holistic approach to both brand and performance marketing as is now possible in audience targeting and campaign planning. Advances in ad platform tech like sequential messaging and dynamic creative mean that customers can be targeted with messages that most accurately account for their current situation, their position in the sales funnel and the cumulative knowledge about that user, based on the historical data touchpoints to-date. Looping back to Les Binet’s fundamental definition of advertising as follows:

  1. Broad reach ads that people find interesting & enjoyable
  2. Targeted activation that they find relevant & useful

Branding ads that are interesting and enjoyable, and performance ads that are relevant & useful. Historically this split is broadly accurate and useful when the dichotomy between Above The Line and Below The Line is rigidly in place, as it assumes that when the customer cannot be directly influenced to make a purchase (and one that would not be tracked) then they should be made to feel interested and joyful instead. This strategy still persists today, with Nike rarely talking about their trainers say, but rather showcasing their sports partnerships which they continue to do successfully decade after decade. Even Nike however understands the power of performance marketing in support of a well-honed brand marketing strategy, one working to the benefit of the other and vice versa. Les Binet and Peter Field proposed the ideal split between branding and performance (fig.6) in “The Long And Short Of It” (2013):



This 60/40 split is based on a study of 996 API cases over 30 years and is statistically viable only within this scope. Some brands should and do spend more than 40% of their marketing budget on performance ads, as this split can vary largely by vertical, company age and prevailing marketing trends.

Whatever the split for your brand/s, the important piece here is that both types of advertising should have a concerted focus and that both types should be approached in the same strategic framework wherever possible. This strategic framework is enabled by advances in tech and ad platform functionality, with media platforms now inextricably linked by measured audience touchpoints, it is possible to deliver the most suitable creative based on where the user is currently in the sales cycle:



This example (fig.7) simply illustrates the strategic considerations for a typical sales cycle. When considering the beginning of this cycle (or Top Of Funnel) we should equally consider the actual purchase point (or Bottom Of Funnel) and join the dots between them both. When joining these dots, the creative execution at each stage should help to move a customer along the cycle, employing both messages that inspire interest and joy, then those that are relevant and useful. It is the understanding of the data points along this cycle that will improve sales and create campaign efficiencies. The sheers size and scale of this data, as multiplied out by the number of total sales cycles, is then the complex problem to address, solvable only with the best technical solutions and most experienced team at the helm. Once solved, marketers then focus on optimisation.


Campaign Optimisation

Campaign optimisation is most often considered by marketers in a digital advertising scope. Optimisation is normally connected to basic digital tactics like changes in targeting segments, bid adjustments, or ad copy tweaks, as this is where the majority of optimisation takes place, is even fully automated in instances. However, this article has shown the key importance of treating both brand and performance marketing with the same focus and effort, as only when both types are approached in tandem and activated strategically together, will campaign success be made certain.



This study by Analytic Partners (fig.8) helps to demonstrate the value in combining platforms which sit at different ends of the traditional sales funnel, here showing a 35% increase in ROI from TV and Online Video as the top performing combination. ROI is a campaign success metric however that is difficult to apply in every instance, across every platform, so we should look to more holistic metrics that are better able to measure impact on the customer, based on the specific channel.

The starting point to do this would be to redefine some of the terms associated with the traditional sales funnel:



The above example (fig.9) helps to show that with a slight shift in how we define and understand the phases in the sales funnel, we can redefine some of the success metrics based at each customer phase. Tom Roach (Jellyfish) suggests updating the 3 phases from Awareness, Consideration, Conversion to Building, Nudging, Connecting, which also helps to unify both ends with the improved understanding that purchases can happen at the top, and that brand can be built at the bottom. The new objectives proposed are “mental availability” closer to the top and “behaviour” (normally understood as purchases) closer to the bottom. The new objectives naturally lead to new example metrics including spontaneous brand awareness, spontaneous purchase intent, search visibility etc., separated out as most relevant as per the customer phase. This is an improvement on the previous model certainly when analysing both brand and performance marketing, but still creates a clear divide between the two based on the geometric confines of the visualisation. Instead we should incorporate the improved definitions into a new model (fig.10) one which visualises brand and performance marketing as rather two distinct sides of the same funnel, applicable to the same customer phases as required by the marketing strategy:



This is important from a strategic standpoint as it enables brand marketing to be considered tactically within the Connecting phase, and then performance marketing to be considered tactically at the Building stage. This 3-dimensional framework then also allows us to track both “mental availability” and “behaviour” in a branding or performance setting.

This is increasingly important as more and more sales conversions are happening in shorter sales funnels, for example, a customer state of “this app looks fun”, then moving through the funnel to the final conclusion “I’ll download it,” is actually happening in seconds or minutes, not in weeks or months. So from a campaign activation and optimisation perspective, ad messages need to be delivered fast. It is rather the seesaw tipping moment between “mental availability” and “behaviour” where marketers need to focus their best efforts. These efforts will involve the best combinations of brand and performance marketing effortlessly nudging the customer along toward a purchase; and these combinations of ad type, funnel phase, channel, platform and creative will only be best optimised by fully understanding the data and mapping it correctly in respect to all available touchpoints.


Learning and Improvement Loop



Here (fig.11) is a simplified view of some of the process considerations that exist when optimising a campaign. It is not complete, nor in a steadfast order, but included here to show the typical areas of marketing where data touchpoints exist that can be measured, extrapolated and learned from. Each contains a wealth of data, including and far beyond those directly relevant to customer “mental availability” and “behaviour”. From a brand and performance marketing point of view, these extra data points will be less viable, interesting sure, but less able to shape a strategic combination between the ad types.

What is of key importance is that the process is endlessly looping; not only for the data touchpoints we have explored in this article, but across all process areas, however distant from the ultimate campaign goal. Furthermore, it is not solely the process areas of where the data is available that need to be constantly revisited, but also the collection methods and understanding methodology that is employed each and every time. For one campaign a combination of Search and TV may produce the best results; but for another, this effort could be better spent on improving the website UX or updating the CRM structure. Whatever it is, it is only knowable and predictable by using data, and it is this data that is the lifeblood of any successful marketing project.


In Summary

To conclude, the traditional sales funnel still has a place in modern thinking when applied to brand and performance marketing, but has gone through a number of iterative changes to-date and will likely go through many more. Its enduring popularity (now in its 124th year) is most likely to do with the simple appeal, it being a basic shape consisting of a few easily understood human mental conditions. The real-world truth behind the sales cycle is that it is never simple, never fully knowable at a single customer level, as human beings are anything but simple. Indeed to call someone simple would be insulting, to claim to know the inner workings of someone else’s mind would be unnerving and swiftly refuted, and to boast that you can make someone buy something by pushing them through a funnel would be considered ridiculous, and yet this is exactly what does and will happen. At 77Agency – Jakala we do not claim to have reinvented any fundamental marketing principle, our aim is to rejuvenate any theory with the best possible data strategy. Our experience exists in the data, and this article helps to show that by better understanding data, we can reshape the time-honoured sales funnel into a more relevant one, one more easily optimised for greater marketing success. Regardless of where your company journey is, either a global brand, top of mind in all your categories, or perhaps, a nimble start-up approaching a performance plateau, both companies will benefit from constantly reviewing its approach to brand and performance marketing. Data itself is infinite in scope, so it will always be the actual understanding of it and the way in which it is used, that produces the best results. It is this final consideration to takeaway, to consider just how to combine data in the most meaningful and insight-creating ways. The improved framework here is useful from a macro perspective, important to relay onto stakeholders and peers alike, but does not demonstrate any actual, live or historical examples. To see this framework in action for your company please contact us on the channels at the end of this paper.

For now, the sales funnel can be reimagined in the following way (fig.12) with brand and performance marketing providing two separate sides of the same funnel, with the funnel itself being made of measurable data points, enabling both mental availability and buying behaviour objectives with the same strategic effort.



(fig.12) Evolution of traditional sales funnel into inverted pyramid made of data points. Final visualisation allows for greater strategic consideration, simultaneously across brand marketing and performance marketing for both mental availability and buying behaviour objectives.


In conclusion, it has never been more important to fully understand the current complexity of the customer journey. The average person sees between 4,000 to 10,000 adverts each and every day (*13), and if each of these are frequency capped at 3 per day say, then that is a total number of 3,333 different campaigns every day. Each of these 3,330 possible campaigns have their own unique marketing strategy and objectives, and the ones that deliver the best results are the ones that are constantly trying to create that perfect balance between brand and performance marketing. This balance is only achieved when the data is understood and acted upon in the right way. This understanding must be accessible by all company stakeholders, and not left solely in the domains of the optimisation algorithms and data scientists, so that success can be demonstrated (and learned from) beyond basic campaign KPIs, at a depth that shows how micro changes at an individual customer journey level, will have an effect on the whole. Our purpose is to make your data known, to clearly explain what action will lead to what effect, and to illuminate the constituent parts of your marketing in order to create a brighter understanding, and a more successful future.




  1. (Fig.1) The AIDA Model -Essential Marketing Models
  2. (Fig.2) Awareness>Consideration>Conversion (ACC) Funnel -77Agency
  3. (Fig.3) ACC Funnel plus Brand-Performance -77Agency
  4. (Fig.4) ACC Funnel plus ATL-BTL -77Agency
  5. (Fig.5) Hexagon screenshots -77Agency
  6. (Fig.6) 60:40 Split –The Long And Short Of It, Les Binet and Peter Field
  7. (Fig.7) Example of possible customer journey and platform touchpoints -77Agency
  8. (Fig.8) Incremental improved ROI from combined media –Analytic Partners
  9. (Fig.9) Modified Funnel –Tom Roach, Jellyfish
  10. (Fig.10) 3-Dimensional Funnel -77Agency
  11. (Fig.11) Learning and Improvement Loop -77Agency
  12. (Fig.12) Reshaping the Funnel for a Data-Driven Strategy -77Agency
  13. * Finding Brand Success In The Digital World –Jon Simpson, Forbes


About 77Agency – Jakala

77Agency was acquired by Jakala in 2020. Jakala Digital & Media Division offers media & advertising, social media, web development, digital PR, creativity & design and SEO solutions. Jakala has offices in 15 countries, running projects in 50+ countries, looked after by 1,600+ team members.