Tag Archives: artificial intelligence

Human satisfaction: Can a bot fake it?

This article was originally published on Inman News:

Excitement about new technology in real estate is usually followed by long delays in practical application. Logistical, territorial and legal hurdles often stand in the way.

Bots seem to be overcoming those barriers with ease.

How do bots work in real estate?

Bots in real estate create artificially enhanced relationship management. From conversation to conversion, nurture and management, software systems are being built to interact with end users as if there was a relationship with a human on the other end.

Sometimes these systems tell the consumer interacting with them that they’re a bot. Sometimes they don’t.

In some cases, they’re a little bit of HAL 9000, assisted by a little bit of Dave the human.

The gray area creates an interesting question: how much “faking it” is ethical — and how much does the end user care?

No doubt you’ve seen “the scene” from When Harry Met Sally. (Millennials, go YouTube it — maybe not at work.)

The conversation centers on whether participants in a transaction can really tell whether or not their counterpart received the desired experience.

Actor A may feel like he has achieved a win-win outcome, while Actor B may just be humoring his obliviousness. Not unlike a parent letting a child beat them in a game to deliver pleasure through illusion, “faking it” is sometimes the most pragmatic decision.

When Riley met Jenny

When the transaction is business-to-consumer, faking it may often be preferable. If a bot can provide a human-like experience with a fulfilling outcome for the consumer, isn’t everyone better off?

Meet Riley. He is a combination of bot and human, but he doesn’t like to talk about it.

Consumers, by and large, don’t know he’s “human-assisted AI.” An inquiry to Riley about a property may begin with some standardized questions and replies. Quickly, though, it transitions into an actual human experience.

Riley’s job is to answer questions and keep the consumer in conversation with value and time that the agent or business-person may not have at the moment.

I conversed with Riley a few times, looking for the moment where the contextual intelligence of a real person took over.

It’s a smooth transition. Most consumers probably aren’t skeptics, looking for the seams in the process.

Even if they knew, though — would they care? Probably not, if the outcome they desired had been delivered.

Call 867-5309 for a good showing

Jenny has a different point of view. She’s built on IBM’s Watson technology, 100 percent bot, and proud of it.

Not afraid to answer 20 texts or Facebook messages at 3 a.m., she wears her digital brain on her sleeve and tells consumers who she is upfront.

It’s a good bet that consumers will be more willing to barrage a bot than a human with extensive and repetitive inquiries.

Jenny’s job is to quickly dispense of the most mundane listing maintenance duties: answering sign calls about property details, showings, flyers, open houses and so on.

Her primary goal is to make the listing management system efficient. Call her Lucy, Clippy or TI-85 — it doesn’t make a difference. Consumers know she’s a bot.

Will Jenny’s upfront AI admission limit other opportunities?

She could transition to lead conversion mode mid-conversation. Already knowing that they’re talking to a bot, though, consumers would probably be less likely to answer a long string of questions about themselves.

Then there’s that nagging truth about real estate: Human loyalty generates long-term clients and referrals. Consumers who feel that their agent has personally provided his or her time to them will often feel obligated to work with, and refer other clients to, that agent.

The giving of human time — real or perceived — generates loyalty. Can a self-identified bot deliver the same feeling?

Team in a box

A team of bots seems like the ideal setup for efficiency.

Riley is mum about his AI to improve the consumer’s experience in the initial conversation. He is the lead conversion bot.

Jenny is the card-carrying bot office manager, delivering answers efficiently with a machine learning badge.

Sally is the incognito sphere nurturer who leans heavily on the real agent for support.

The level to which they support one another or reveal themselves as inhuman will depend on the ethics, perception and aggressiveness of their employers.

Of course, technically, these bots don’t have to be disconnected entities. They’ll likely be built as a single software program with different personalities for different duties.

Call it a team in a box. Defining the personalities is the key to optimizing the user’s perception.

The technology is already capable, but the personal nuances will determine consumers’ acceptance of the experience.

“You don’t think that I can tell the difference? Get outta here.”

Harry didn’t know until he was told. Will consumers know — or care?

A quick note:

CRMLS has begun passing on listing licensing fees from third-party portals to its member brokers. Bravo! The dollar amount is minuscule today, but the decision is still significant.

CRMLS can’t disclose which portals are paying for direct feeds, and how much they’re each paying, due to contractual obligations. This isn’t a surprise. I’ve been asking around the industry for years and getting jazz hands as a response.

The spotlight is beginning to shine through the smoke and mirrors of listing syndication finance. How much will portals pay for a listing? How much is that listing worth in ad revenue? How many MLSs are being paid by portals, and how many are willing to pass that revenue on to the brokers?

Why not create a model where the portal pays a referral fee to the broker/MLS based on a percentage of advertising revenue generated? Brokers know they’re not leveraging their listings’ advertising value. Creative options for greater revenue capture will continue to grow as broker margins shrink.

More exposure of these kinds of financial agreements is good for real estate. Pricing is arbitrary when sellers don’t know the market value of their product. Let’s continue to air out the details.

Sam DeBord is managing broker of Seattle Homes Group with Coldwell Banker Danforth and President-Elect of Seattle King County Realtors. You can find his team at SeattleHomes.com and BellevueHomes.com.

Artificial Intelligence (AI) in real estate: Negating or monetizing an agent’s experience?

This article was originally published on The Real Daily:
by Sam DeBord

Have you ever emailed or texted someone, and subsequently opened Facebook on your phone to immediately see that person in your news feed?

You read the entire terms of service when you downloaded that app, right? So you remember agreeing to every bit of your phone’s hardware and software recording and interpreting the signals that your everyday actions are creating (just nod your head yes—it’s watching you right now).

Artificial Intelligence is seeing tremendous growth in consumer-driven industries. It is the ability for software to learn and adapt to consumer behavior via live feedback. Cars, websites, wearables, and apps are becoming more intelligent and adaptable.

We’re seeing huge advances in the affordability of AI software that match the exponential growth of hardware’s computing power.

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Simultaneously, human labor in developed countries is increasing in cost. Minimum wage laws, increasing liability, and rising health care costs are pushing employers to replace labor with technology. McDonald’s employees become kiosks that order Big Macs. Chase Bank tellers are replaced by apps that scan and deposit checks. Companies like Circuit City and Borders Books shutter their stores as websites more efficiently serve their customers.

How AI intersects with RE

Intelligent software has massive potential for creating technology that changes labor markets. Real estate labor is a natural target, and a couple of recent pieces got the ball rolling this past week.Russ Cofano penned a broker outlook that viewed “cognitive computing” not as a threat to labor, but an asset to the baseline of real estate’s agent intelligence:

“So here’s the question. What if cognitive computing enables agents to be better professionals and make better recommendations to their clients? What if access to cognitive computing power, and the data necessary to power it, becomes the 21st century equivalent of the MLS utility?”

Further, Cofano states, “Cognitive computing has the potential to add massive value to the real estate brokerage value proposition and do for agent professionalism what no other initiative could touch.”

While the piece focused on the superior delivery mechanism (Upstream vs. the MLS), it provided support to the idea that brokers could adopt intelligent data systems to improve agent capabilities industry-wide.

Not surprisingly, a different take came from Rob Hahn, focused on the costs of repetitive labor and the likely evolution:

“The $6 billion question is where real estate brokerage services fit in the spectrum of services if we put McDonald’s order-taker on the one extreme and the Chief Engineer of Nuclear Fusion Reactors on the other extreme in terms of specialized skill and knowledge.

I think most of my readers know the answer. Real estate is far, far closer to McDonald’s than it is to McDonnell-Douglas.

…rote procedures and manual inputs are being displaced by technology. Why would it be any different for the rote procedures and manual inputs in the real estate business?

Answer: it won’t.

Those real estate agents who survive will have to be ‘upskilled’ and focus on niche areas or ‘be equipped to handle smart systems.’”

Comparing two views on AI

So we have two very different views of software intelligence’s effect on real estate agents. In one, brokers might adopt cognitive computing measures to improve agents’ core capabilities to serve consumers. They improve and survive as a unified group of forward-thinking adopters.

In another, AI wipes away the entire foundation of repetitive services performed in real estate. This debases the masses of agents and eliminates the need for their services. It leaves only the specialized practitioners above water when it’s done.

It would be remiss of me to gloss over the McDonald’s analogy. The skills that allow agents to survive in their occupation can’t be crammed into a single linear comparison. It seems prudent to point out that the comparison of rocket scientists, real estate agents, and Egg McMuffin order takers should be complex.

In recent real estate history, replacing a repetitive procedure in the sales process with software has simply changed the sales process. It hasn’t removed the sales person. There are graveyards full of real estate labor would-be disruptors who have a poignant understanding of that history.

artificial-intelligence-REAL-ESTATE

The intrinsic skills that keep real estate agents strongly entrenched in the industry seem to center on two things:

  • Personalized intelligence (unique local knowledge, negotiation, transactional experience)
  • Personal relationships (emotional IQ and sphere building)

The latter is almost invariably ignored in real estate labor disruption conversations, yet it’s probably the single greatest barrier to disruption. People list with people. Sellers’ top three requirements for a listing agent are reputation, honesty, and trustworthiness.

AI is the intrusive stalker in your phone. Thelma is the amazing woman who comes to book club and walks with you on weekends. H.A.L. 2000 can’t touch her in terms of trust. This should be the overriding theme of every disruption conversation.

On to bottling knowledge

In the future, personalized intelligence might be a different story. If part of the value of exceptional agents comes from what they know from experience, the way they negotiate, and how they interact with clients, how much of that could be learned by an exceptional AI platform?

Could exceptional agents allow themselves to be profiled by their devices and capture that intelligence to monetize it? Would brokers be able to conglomerate the practices and intelligence of their best agents to provide a unique set of processes for their agents and answers for their clients that aren’t available to the general public?

It might not be as crazy as it sounds. Think about the vast amount of information that could be gleaned from one agent over a single year with all of his/her devices in “AI learn mode.” Spoken word, tone, movement, visual cues, timing, location data, digital communication, social engagement, contract negotiation—all of these and more could be processed into a database describing when, where, and how top agents interact with their environments to close more sales transactions.

Who owns the AI?

While the aforementioned could be done on an industry-wide basis to inform brokers as a whole, it might also be led by savvy top producing agents or brokers who would profit from it as a differentiator. Melded with predictive analytics on consumer behavior and market statistics, the right set of personalized intelligence could tell an agent when and where to meet a consumer, and how to begin interacting with that person to provide a greater likelihood of a client and a sale.

Of course, until personality can be direct-ported into the agent’s brain, we still need a human with emotional IQ to show up and close the deal. The creation of a relationship might be initiated by data, but it’s going to be sealed with emotion.

ThelmaRealtor software version 2.5 could be an AI profile that’s sold to brokers or new agents as a foundational of intelligence for their careers. Whether these benefits and profits go to the real Thelma, her brokerage, or the industry depends on who adopts the technology first.

Back to the people

If that’s all a bit too much sci-fi, let’s get back to the basics. There are huge opportunities for the brokerage community to leverage greater technology and AI to improve how they do business. Those that do will have valuable differentiating tools and skills.

Still, Thelma v. 2.5 isn’t going to wipe out the physical agents on the ground. Technologists with armies of software agents will continue to stare at screens, while real life agents are cementing unbreakable relationships with real people. Consumers will work with agents they view as trustworthy, no matter what amazing intelligence is dangled in front of them by H.A.L. 2000 Realty.

It’s true that consumers want more intelligent real estate transactions. Before that, though, they want trust. AI has great prospects for helping brokers and agents improve their business intelligence, but it’s not going to take the human element out of the transaction any time soon. The real Thelma’s role may change, but she still owns the most valuable, subjective, and defensible portion of the real estate transaction: the relationship.