Household Cash Flow and Company Revenues


This blog seeks to understand the interaction between household cash flow and company revenue. 

Carraighill’s investment approach seeks to understand a company’s operations in the context of its ecosystem. This involves a deep dive into all available data sources, structuring the output in a way that is simple to understand and unlocking the key investment drivers for a specific sector or stock. There are many factors that influence performance and this can be an exhaustive process.

After this we are in a better position to understand a company’s marketplace, its key competitive advantages, and its challenges. It also permits a more insightful discussion with a given management team.

This has always been a more logical investing approach to us. It also means we can focus on both the long-term structural view (1-5 years) and shorter-term cyclical factors (up to 12 months).

What do we mean by a deep dive into the data? 

In this diagram we demonstate how several companies’ revenues are directly impacted by only one single component of a country’s economic structure: Household cash flow. We show how it logically works into the topline of: 

1. Retail and Office REITs: Example: Gecina, British Land, Unibail, Klépierre 

2. Payment Companies Example: Nexi, Adyen, Worldline, Stone, Paypal. 

3. Consumer Lending and Banks: Example: Unicredit, BNP, Commerzbank, BBVA. 

4. Instore and Online Retail Example: Ocado, Next, Tesco.  


Source: Carraighill (may not be copied without express authorisation of the provider).

Two simple (shaded) examples include:  

Example 1: The impact of WFH trends on London office occupancy: Under Margaret Thatcher, the UK transitioned from a manufacturing-based economy to one based on higher value-added services. This allowed the City of London and related companies to thrive, especially some of the largest office and retail landlords. Although the post Brexit economic outlook is still uncertain, increased working from home trends are now posing some key longer-term risks to landlords. This trend is most evident in service-based economies. If it persists, the implications are potentially profound. For example, the ONS has surveyed businesses on whether they plan on making WFH permanent. If we weight this to the percentage of the workforce in Central London in these service industries, we can estimate the potential impact on office occupancy from 1 day per week, 2 days per week, etc. away from the office. We believe that each day reduces potential occupancy by 6ppts. This will influence Office REITs.  Once we understand this structural challenge, weekly footfall data allows us to understand the cyclical position. This impacts how we think about rent on a longer term and shorter-term basis. This will influence office values.

Example 2: Consumption items and its implications for online and instore retail salesCarraighill has developed a proprietary estimate of online penetration across Europe. We have dissected consumption and retail sales data by itemThis helps us to appreciate: 

1. The extent and pace of the migration online in total and in core product areas. 

2. The €/£ bn size of the market opportunity for internet-based distribution (this can often be difficult to specify as many datasets use index measures). 

3. The topline pressure on existing instore retail and the implications for high street and shopping centre rents.  

Our database has monthly data extending back for over a decade. Key insights include: 

  • The proportion of output executed online has been structurally rising over the last decade in all countries. In Europe, Czechia has the largest share (high 30%’s) whilst Italy lags. This may reflect Italy’s older demographics and lower internet penetration level. 
  • Within the UK: 
  • Online food represents close to 30% of the total retail basket on average. The share of output executed online has been growing, but the penetration is still only annualizing at a low double-digit percentage. As the largest spend item, the online opportunity for companies in this area appears large.  
  • Clothing and footwear (close to 20% of the basket) has a higher online share (over 30% in 2020f).  
  • Other retail (furnishings, computer electronics, and other items) represents close to 50% of the basket, with close to 30% now executed through e-commerce channels. 


  • One factor that will influence the global opportunity for online and the vulnerability of instore retail by geography is the consumption mix (food, clothing, other retail) within each country’s retail basket. For example, Italians and UK citizens spend a larger proportion on footwear and clothing. French citizens spend proportionally more on food. The UK has a greater share on discretionary items in its retail basket, and so is more cyclical in downturns. 



If you would like to discuss any of the items mentioned in this article, Carraighill Research Access enables you to access these and other thematic and sectoral research through our secure online portal. If you would like to speak to a partner or analyst on the topics raised in this piece, you can contact us here.

Carraighill Expert Opinion