How to optimise marketing budget allocation in B2B firms

The potential of marketing budget allocation to drive top-line growth and profitability is significant and has been widely proven. Analyx, a company specialising in budget optimisation, has successfully implemented its approach with marketing budgets in various B2C projects. These have demonstrated that companies can achieve between 0.5% and 3% additional revenue growth without expanding their marketing budgets. Alternatively, companies can make significant efficiency gains (20–25%) in their marketing spending without losing revenue. Media mix modelling (MMM) has become established as the data-driven method of choice to enable quantitative optimisation of marketing budgets and perform what-if analysis of different media mix strategies.

These models use statistical techniques to analyse the relationship between marketing activities and business outcomes, providing insights into the effectiveness of different marketing channels and strategies. 

MMM has traditionally been applied in B2C industries, especially in the fast-moving consumer goods (FMCG) sector, with several successful case studies demonstrating its impact on driving top-line growth and profitability. However, there are a number of challenges to applying MMM to B2B marketing, specifically in the context of Professional Services.

1. Lack of data in B2B hinders accurate measurement of marketing impacts
   The main challenge to using MMM in B2B marketing is the lack of available data, as B2B sales cycles are longer and involve a more complex decision-making process than B2C transactions. This lack of data can make it difficult to accurately measure the impact of marketing activities on business outcomes. There is also often less variation between different B2B products and services than with B2C, making it harder to identify the specific factors driving sales.
2. Measuring the impact of professional services on business outcomes is complex
   Professional services are both complex and intangible, which makes it challenging to measure their impact on business outcomes. In this context, the traditional MMM approach may not be sufficient to identify the full range of factors influencing the customer’s decision-making process.
3. Demonstrating the effectiveness of media mix modelling
   Although MMM has traditionally been used in B2C industries to drive top-line growth and profitability, demonstrating its effectiveness in B2B presents a challenge. To showcase its potential in professional B2B services, PwC Switzerland and Analyx collaborated on a proof of concept to optimise marketing budget allocation and maximise new leads.

The PwC marketing teams are responsible for promoting the company’s comprehensive range of services. The focus of the teams is to optimise promotional activities, ensuring that the right campaigns reach the right audiences at the right time to drive PwC’s growth. To achieve this goal, PwC’s marketing teams leverage a balanced combination of communication channels and advanced technology to effectively reach and engage their target audiences. They closely monitor and analyse marketing metrics and campaign performance, employing a data-driven approach to make informed decisions and optimise future marketing strategies.
In 2017, PwC underwent a significant marketing transformation by completely overhauling their approach to focus on a more human-centric strategy. To reach the full story, click here.

As a B2B consulting company, PwC faces similar challenges to other B2B enterprises in implementing an MMM approach for its media budget strategy: lack of available data, the complexity and intangibility of professional services, and the need to demonstrate the value and marketing return on investment. Overcoming these hurdles is a crucial aspect of PwC’s marketing efforts.

PwC Switzerland therefore collaborated with Analyx on a proof of concept to showcase how MMM can be used to optimise the allocation of paid media budgets and identify the marketing channels that generate the highest number of leads. This partnership enabled PwC Switzerland to successfully overcome challenges in the context of B2B professional services, taking a data-driven approach and utilising innovative marketing strategies to stand out from the crowd and stay ahead in a highly competitive market.

To set up the MMM, the project team used data from Salesforce’s Marketing Cloud Intelligence tool, which was already in use at PwC. The marketing team has been using this tool on a regular basis to report more effectively on marketing campaigns. Click here to read our case study.

This approach allowed the project to be implemented more quickly, as it provided structured data for use in the MMM analysis. The objective was to determine how the paid media budget should be spent to maximise the number of new leads generated for PwC Switzerland. A lead was defined as an individual who had expressed interest in PwC’s services and did not have a business relationship with the company. Consequently, the number of new leads shows how the overall number of leads generated changes during a given time period.

The overall budget for paid media was distributed among several key channels, with LinkedIn Ads, programmatic advertising and search engine advertising (SEA) representing 94% of the total. The remaining 6 % are grouped as other marketing channels, including Google Display, Twitter Ads and native advertising.

To better isolate their impact on new leads, other factors such as seasonality, sponsored events, SEO visibility and email marketing were also considered in the model.

To ensure an efficient setup process, the project team relied on Analyx MMM, a leading European MMM solution. Analyx MMM was well-suited to the project due to having the following features:

1. Comprehensive activity tracking: Analyx MMM incorporates non-media activities such as email marketing and events into its models to provide a more accurate assessment of overall marketing performance.
2. Predictive modelling capabilities: Clients can run predictive what-if scenarios to assess the impact of different marketing strategies and optimise their budgets accordingly.
3. Advanced optimisation algorithms: Analyx MMM uses the latest techniques to help clients optimise their budgets across their portfolio of marketing channels.
4. Customisable performance objectives: Analyx MMM allows clients to set and maximise their volume, revenue or profit targets based on their specific business goals.
5. Long-term brand impact analysis: The platform factors in the long-term impact of marketing campaigns on brand awareness and equity, allowing clients to make more informed decisions about their marketing spending.

Data was initially collected using Salesforce’s Marketing Cloud Intelligence solution. This data was then exported and utilised for the MMM analysis, which was conducted by Analyx. Integrating these two platforms allowed a comprehensive evaluation of PwC Switzerland’s marketing efforts and their impact on generating new leads.

To ensure the quality of the underlying models, the project team used the mean absolute percentage error (MAPE) in addition to the commonly used R². The MAPE serves as a metric to measure the percentage of deviations between observed and predicted values in an average week. With a MAPE of 14.3 %, the model’s accuracy was 85.7 %. Although this exceeds the typical MAPE of 7–8 % achieved in B2C, 85.7 % accuracy is still a solid result within the B2B context.

The analysis revealed that paid media activities contributed 7 % of the new leads generated.

Of all paid media activities, it was observed that LinkedIn Ads was the most influential channel, while programmatic advertising had the least influence on generating new leads. Conversely, various other factors collectively had a very significant impact, generating 93 % of new leads. These factors included seasonality, events, and additional digital marketing endeavours, such as SEO visibility and email marketing. Among these factors, SEO stood out as having a particularly substantial influence.

Based on the analysis, Analyx recommended a revised budget allocation strategy for the paid media budget, which included the following:

• 29 % budget increase for LinkedIn Ads
• 11 % budget increase for SEA
• 50 % budget cut for programmatic advertising
• 10 % budget increase for other channels

The media mix optimization analysis conducted by Analyx demonstrated that by allocating the paid media budget optimally across various channels, it is possible to increase new leads by approximately 0.9% while keeping the budget constant.

These findings show how crucial it is to understand the impact of each media channel and optimise the paid media mix to achieve the best results. Overall, the project successfully identified the ideal paid media mix for PwC Switzerland to maximise the impact of their marketing budget on generating leads. These insights will empower PwC Switzerland’s marketers to increase the effectiveness of their paid marketing budget.

Modern MMM is not just for B2C industries! With the right methodology, data and technology, B2B businesses can also benefit from the insights provided by MMM to optimise their marketing expenditure and drive growth. In this case study, we have demonstrated that implementing MMM can provide valuable insights into the effectiveness of marketing channels in creating new leads for a B2B business. By analysing historical data and incorporating other factors, such as seasonality and events, we were able to isolate the impact of paid media activities and identify the optimal media mix for generating new leads.

• One key takeaway is the importance of selecting the right target variable. It should be closely related to the impact of media and have a direct impact on the business’s profit and loss. In this case study, the target variable was new leads.
• It’s important to note that B2B businesses can more easily measure their impact using MMM if they rely more on digital paid media channels such as LinkedIn Ads and programmatic advertising, and less on offline activities such as events and conferences. This is because the data is more easily accessible.
• Analyx’s MMM showed a high level of accuracy, with a MAPE of 14.3 %. The analysis revealed that paid media activities contributed 7 % of new leads; LinkedIn Ads was the strongest individual channel, contributing 3 % of all new leads. Among the other factors that help generate new leads, SEO had a remarkably large impact.
• Finally, and most importantly, the media mix optimization conducted in this case study revealed that by reallocating budgets among paid media channels without changing the overall budget, new leads could be increased by approximately 0.9 %.

Authors

We would like to thank our PwC Germany colleagues for producing this case study: Mathias Elsässer, Julian Röhl, Sascha Stürze and Stefano Belardi.

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