This post is the latest in a weekly series of excerpts from BIA/Kelsey’s recent report on the Local On-Demand Economy (LODE). The series will lead up to BIA/Kelsey NOW, a conference on LODE that will take place June 12 in San Francisco.
What’s next for the Local On-Demand Economy (LODE)? Though it’s been the recipient of lots of investment and media attention (including our own coverage), much of that has focused on where it is now, and where it’s been. But what about where it’s going?
As LODE engenders an ecosystem of supporting functions, there will be entry points for business opportunities. That includes everything from app development to back-end systems that run LODE products. And there’s a big opening for existing local media companies as we covered last week.
As far as supporting functions, we discussed a few of them on last week’s LODE roundtable, including the logistical systems that will help achieve LODE’s primary end: to algorithmically connect buyer and seller. There are lots of pieces to that value chain such as scheduling, payments, CRM, etc.
Similarly, our recent white paper covered some of these potentially opportune areas that are adjacent to LODE. An excerpt of the relevant passage is below, and stay tuned for lots more on this topic.
Local On-Demand Economy: The Future
As LODE expands, its capabilities and fusions with adjacent areas of technology will grow. It will support and be supported by many parts of a growing ecosystem. Areas we’ll examine here tie directly to monetary dynamics: demand pricing, mobile payments and growth through APIs.
After LODE grows in usage, vertical expansion and solid footing (phase I), its second phase will be to optimize pricing for maximum revenue. It will begin to do this by ingesting and processing large samples of consumer behavioral and spending patterns. The age of big data meets LODE.
The idea is that all of the signals emanating from the mobile device and processed through apps can be the building blocks for dynamic pricing. This goes back to Brendan Benzing’s quote in an earlier section that LODE’s demand aggregation is a play towards yield management.
For example, knowing how far away someone is to a business — and several other variables — enables predictive modeling about their probability of transacting. This isn’t necessarily new but takes on new flavors if worked into an equation that defines their price sensitivity or elasticity.
From there, the potential is to offer different pricing to existing customers, repeat customers, faraway customers, nearby customers, customers with green eyes and a love of craft beer, etc. This gets us closer to mobile’s promise of more effectively driving offline commerce.
The idea is to segment consumers by willingness to pay for something — a function of location-oriented factors like weather, behavior, time, product category, etc. This makes it a juiced up version of the airline model that maximizes revenue with demand-driven variable pricing.
It’s especially relevant within the context of perishable inventory (empty movie theaters, restaurants, etc.). This is of course nothing new, and gets to the yield management endgame of the daily deals craze of 2010. But in volume and depth of data, LODE will better enable it.
Of course the LODE poster child has already planted this stake. Uber’s “surge pricing” is dictated by demand levels in certain neighborhoods. It not only maximizes revenue during high-demand moments, but it compels supply (drivers) to log in and move towards “surging” neighborhoods.
We’ll see some version of surge pricing become a core tenet of existing LODE apps/services, and those still to be developed. This is most ripe in areas with volatile demand, price inelasticity and temporal relevance. Urban or event parking, for example, is an area where dynamic pricing could develop.
BIA/Kelsey has a cautiously optimistic view of mobile payments. There are consumer acclimation and retail implementation challenges. And network effect is required to gain scale and compatibility on each side of this equation. It’s a classic local “chicken & egg” challenge.
But this mostly applies to offline retail (POS) payments. Since using Apple Pay all over town, BIA/Kelsey has realized the lower barrier play where mobile payments’ near-term opportunities lie: in-app payments. This doesn’t have the same compatibility hurdles (hardware) as a physical POS.