Jan 30, 2023

Vertical search for building materials

Artificial intelligence (AI) seems to be the latest catch-all that venture capital investors are in love with – following “FBA aggregators” in 2020, “Web3” in 2021 or some fundamentally stupid “climate” stuff that also got backed in 2022.

I do think applied AI holds greater promise than many of the aforementioned. OpenAI for example has potential to transform horizontal applications (forcing Google for the first time ever to feel threatened apparently).

But I think applied AI can equally transform vertical B2B sectors.

One such huge opportunity I am seeing is AI-enabled vertical search in construction and architecture, specifically vertical search for light building materials such as floors, tiles, textiles, paints, decor and so on.

When I posted this on Linkedin the other day, a discussion erupted about concrete, cement, steel. Those are heavy “in-the-wall” building materials, which in the mature markets have very established supply chains and market dynamics (that’s different in emerging markets).

For vertical search, my observation is that light “outside-the-wall” building materials make a perfect fit. Categories such as paints, floor, stones, fabrics, glass, bricks, decorative metals, plasters, textiles have more than 250’000 potential EU-based suppliers, millions of customers and millions of SKUs.

Most importantly, the way the discovery, selection and purchasing happens is diametrically opposite to heavy building materials. Consider my framework here:

Framework: Purchasing decisions in light building materials vs. heavy building materials

Buyers of such light building materials know what they want as they have a vision and concept, but need to find specific SKUs.

And for these light material categories, purchasing decisions are made not just on performance and price, but additionally on haptics, optics and increasingly ESG considerations.

Therefore, the industry hotfix practice for the last 50+ years has been to (a) meet at trade shows and display samples and (b) send around samples in large quantities during the early discovery processes. Both practices are not scalable for millions of SKUs in light building materials.

That’s where AI-powered vertical search comes into play.

My dumbed down thesis is that for every “Amazon” in light building materials (eg. Material Bank), which is logistics-enabled and strips manufacturers of their market power, there must be a software-powered “Shopify” that enables manufacturers (eg. Mattoboard, Stylib and others)

The one reinforces the other.

Now applied AI becomes increasingly ready to allow manufacturers to organize their vast SKU catalogues at scale, while it allows buyers to discover one very specific SKU they need for their project without going to a trade show nor getting more samples. At scale !

Hence why I am keen to back founders building the AI-powered vertical search for (light) building materials in mature markets.