Proptech evangelists would have you believe that emerging digital technologies can and will be applied imminently to any real estate use, in the process resolving all of the industry’s current inefficiencies overnight. However, as the saying goes: if something sounds too good to be true, it usually is!

Gartner’s hype cycle (figure 1), explained below, conceptualises the maturity and adoption of emerging technologies, providing a sound source of insight to manage their deployment within the context of specific business goals. 

Figure 1: Gartner’s hype cycle

•          Innovation trigger: A potential technology breakthrough kicks things off. Early proof-of-concept stories and media interest trigger significant publicity. Often no usable products exist, and commercial viability is unproven.

•          Peak of inflated expectations: Early publicity produces a number of success stories, often accompanied by scores of failures. Some companies take action; many do not.

•          Trough of disillusionment: Interest wanes as experiments and implementations fail to deliver. Producers of the technology shake out or fail. Investments continue only if the surviving providers improve their products to the satisfaction of early adopters.

•          Slope of enlightenment: More instances of how the technology can benefit the enterprise start to crystallise and become more widely understood. Second- and third-generation products appear from technology providers. More enterprises fund pilots; conservative companies remain cautious.

•          Plateau of productivity: Mainstream adoption starts to take off. Criteria for assessing provider viability are more clearly defined. The technology’s broad market applicability and relevance are clearly paying off.

Table 1: Proptech applications’ position on the hype cycle

Table 2: Proptech clusters

Each year, Gartner conducts extensive research to accurately position emerging technologies within its hype cycle framework. Table 1 details those technologies it has listed in the last two years and which are also frequently mentioned in the real estate media, including their predicted time until mainstream business adoption will begin. Note that it can then take longer for these technologies to find their specific real estate uses and become proptech innovations. While blockchain, for instance, was first developed in 2008, it was not until 2017 that it reached the top of the hype cycle, and novel real estate startups began to experiment with its industry applications around the same time.

Not content with this indirect analysis, at Oxford University’s Future of Real Estate Initiative we decided to explore more specific proptech diffusion trends using machine learning techniques on funding data from Crunchbase, an online startup directory, and organisational data form Unissu, a database of more than 7,000 proptech companies. The full results from this analysis can be read in our recently released ‘PropTech 2020’ report, while the following results offer a 2019 snapshot of the maturity of the proptech market and its various subsectors.

Figure 2: Funding trends for different proptech clusters

The first step in our analysis was to use a data-driven clustering method to identify various combinations of technologies which are frequently used together by proptech companies, detailed above (figure 2) and labelled according to the areas covered in each chapter of our report.

We would put forward an argument for a seventh cluster, as within ‘analytics’ exist two sub-clusters, namely data analytics and spatial analytics, the latter technologies being the last four items listed in that column. However, to remain consistent with the data, the graph above (figure 2) details only six clusters. It shows how funding into each technology cluster has varied with time. 

Curiously, we identified that these individual funding trend lines follow the same path as Gartner’s hype cycle analysis, allowing us to hypothesise their position with regard to their 2019 market expectations and maturity, as explained previously, and therefore predict which current industry models of operation are most likely to be disrupted in the near term (see figure 3).

What we see is that, using levels of funding as a proxy for market hype, those technologies used in data analytics have transitioned through the full cycle and will probably be the first proptech solutions we see widely adopted by the real estate industry. While the position of the other clusters on the hype cycle graph does not necessarily give an indication of their time to maturity and widescale adoption, it is clear that many of the technologies being discussed today are around their peak of inflated expectations, so 

it is highly likely they will not fulfil the overhyped visions many have for their disruptive potential. However, when we consider Gartner’s analysis, we can see the sheer scale of new technologies maturing within a five- to ten-year time horizon, which suggests that by the end of the decade, things will certainly begin to look a lot different. 

Figure 3: Proptech clusters’ market expectations and maturity 

Amara’s law is so often used by startups in the industry that I have dubbed it the ‘proptech psalm’. However, swallowing my pride, I have to admit that here it does seem somewhat fitting: “We tend to overestimate the effect of technology in the short run and underestimate the effect in the long run.”