Real estate data integration for multi-channel marketing

The tightest definition of multichannel customer management I have yet found is:

Multichannel customer management refers to the design, deployment, coordination, and evaluation of channels through which firms and customers interact, with the goal of enhancing customer value through effective customer acquisition, retention, and development.

Neslin, et al. have authored a definitive research article that real estate firms can use to understand the challenges pertaining to “modern” real estate practices relating to client relationship, and agent relationship, issues. The research paper explores five primary challenges and analyzes the issues pertaining thereto.

Neslin begins by identifying the challenges:

[F]ive major challenges for managers: (1) data integration, (2) understanding consumer behavior, (3) channel evaluation, (4) allocation of resources across channels, and (5) coordination of channel strategies.

This post is first in a four or five part series that will explore Neslin’s position and extrapolate such to real estate marketing and client relationship best practices.

Neslin begins by identifying multitudinous ways by which consumers engage retail firms–from kiosks, call centers, catalogs, bricks-and-mortar stores, etc. Similar interaction vehicles are true for real estate firms–front-yard signs, websites, office walk-ins, etc. Next, Neslin defines “channel”

By “channel,” we mean a customer contact point, or a medium through which the firm and the customer interact.

He then sets the basis for his study: that the focuse of MCM is on the customer, as MCM is a customer-centric function. Neslin next identifies major phases of a client interaction

First, customer perceptions and preferences drive channel choices (e.g., the customer may prefer the Internet for search because it is easy to use). Second, the customer learns from and evaluates his or her experiences, which feed back into the perceptions and preferences that guide his or her next shopping task (e.g., the customer may learn that the Internet search did not answer all the important questions). Third, the customer chooses both channels and firms, so from the customer perspective, it is a two-dimensional choice.

The relevant question then is: to harness this consumer interaction data, what investments must a firm make regarding such? What Neslin argues is that firms do not necessarily have to invest in processes that involve “full data integration” in a quest to develop a “single view” of a customer. What this suggests, then, is that firms must make strategic investments in data acquisition a key points in a transaction.

Real estate firms can leverage key consumer data acquisition “channels” or points. First, any point where a consumer registers for information is a channel. This real estate site contains at least 15 registration opportunities for clients during key phases of a transaction: from beginning (click-to-chat) to contacting an agent to book a showing appointment. Of course, many firms already have this data. So what’s the next step?

Data overlays.

That is, real estate firms should consider augmenting this core consumer registration data with real time, or post-transaction data overlays, from data aggregation companies like Experian, Acxiom, Equifax, etc. These overlays take the form additional demographics, psychographics, household income levels, lifestage, etc, data elements.

Another form of consumer data can be supplied by real estate agents. Although somewhat rare, some agents actually keep client profiles (likes, desires, familial relationships). Why? Because thes agents know that understanding a client’s profile allows them to serve this client (and like clients) at a degree somewhat higher than the norm. These agents use these profiles as their competitive differentiator.

Creating client profiles (either at the per record level, or aggregate level) should be considered a first step for any real estate firm that’s serious about multi-channel management. By using such profiles firms can engage clients at a more relevant and informative level. Thus, maximizing the return on investment the customer is making by spending time on the real estate firm’s site. Similarly, a firm maximizes its own return on investment by allocating tight marketing resources in a more intelligent and cost-conscious manner.

Real estate zip code search optimization

It looks like this company is winning the Chicago real estate search engine optimization strategy and execution race. These representative results speak for themselves: 60647 homes for sale, and 60647 townhomes for sale, and 60647 condos for sale all have this website listed in Google’s top slot (at least as of the date of this post). But what really sends this site over the top in terms of customer service and Internet consumer convenience is its RSS feed.

Breaking Website useability par

As a real estate firm with a sophisticated website, what other websites are your top “competitors”? Obviously, your local market competitors are your competitors. Similarly, certain national aggregator sites are too. But what about non-industry sites? Like eBay, Amazon, Cabela’s, Home Depot, Facebook, etc? Arguably, they are too. Why?

Internet consumers experience a variety Website experiences on any given day. Their online search experience spans from generic to hyper-specific Google searches to specific item searches on sites like Amazon. Chances are that these consumers are more frequently interacting with these latter types of sites than any real estate firm’s site. Thus, these consumers’ expectations for search, interactivity, responsiveness, customer service, etc, are set by these non-real estate industry sites. If your site does not meet par, your site is irrelevant to these consumer (at worst) or an annoyance (at best).

Accordingly, real firms that are serious about meeting and exceeding Internet consumer expectations regarding website usability should study these outside-the-industry platforms, map their site’s current functionality against these other sites, and begin the process of adjusting their sites to step up. Use these other sites’ public-facing operations as tools to learn best practices and adopt relevant processes. Firms, thus, avoid sinking research and development dollars into usability analyses and, in effect, leverage the millions of dollars these other sites have invested in such.

Multichannel marketing forensics

Kevin Hillstrom, President of MineThatData has written an excellent whitepaper on conducting a multichannel forensics analysis. Why is this whitepaper an important resource to real estate firms? Because real estate firms are engaged in complex multichannel marketing endeavors. But only a handful of these firms analyze their data from a multichannel perspective.

How does a firm begin its forensics analysis? Hillstrom explains:

  1. Understand the Retention Mode your product, brand or channel resides in.
  2. Understand the Migration Mode your product, brand or channel resides in.
  3. Combine the Retention and Migration Mode, understand which of twelve retention/migration modes your business operates in. This determines the way you will grow your business, long-term.
  4. Map the Ecosystem, so that the executive can clearly understand how all products, brands and channels interact with each other.
  5. Forecast the Ecosystem. This allows the executive to understand the long-term health of the ecosystem, given various marketing initiatives.

A key point Hillstrom makes is to look at multichannel businesses as ecosystems, where each product and division is interdependent on one another (a biodiversity perspective would also apply). Unfortunately, many companies are still balkanized in this regard.

For the most part, real estate firms have at least centralized their focus around a core product and service: representing buyers and sellers of homes and other forms of real estate, combined with highly related ancillary businesses such as rentals, REO, mortgage and title services, etc. This is a real estate firm’s ecosystem.

Hillstrom, in this whitepaper, has identified several business modes and strategic considerations related thereto. With the exception of certain commercial divisions and investment services, real estate firms fall within one of the two following modes: Acquisition / Equilibrium Mode and Acquisition / Transfer Mode. Both modes imply a constant sourcing of new customers with differences in how customers adopt new products or services. In the case of the former, Hillstrom states customers occasionally migrate, whereas in the case of the latter, the assumption is that customers will migrate to another product (much like a professional baseball player over his career migrates between teams).

So how can real estate firms a) position their products and services more relevantly to new sources of customers while b) targeting the “may migrate” class to the “probably will transfer” segment? Hillstrom advocates mapping the ecosystem

A key aspect of Multichannel Forensics is the mapping of the ecosystem you work in. Each combination of products, brands and channels are mapped. Any relationships in equilibrium or transfer are mapped with arrows, arrows that indicate the direction of the relationship.

The next step is to forecast the ecosystem, which, Hillstrom argues, enables executives to engage in valuable scenario analyses.

The benefit to a real estate firm in undertaking these analytical steps is that it will have a deeper understanding as to how its agents influence (negatively or positively) the firm’s sales of its primary and ancillary products and services. What’s also beneficial about Hillstrom’s whitepaper is that he actually gives you a step-by-step process by which to perform the analysis.

Ranking real estate agents

David Parmet, in a recent interview, talked about how Stormhoek winery and English Cut custom tailoring used social media strategies to promote their new products and brands: Stormhoek blog and English Cut blog. Both brands have a bit a Kula in them.

The salient part of Parmet’s insight lies in his admonition to brands everywhere to embrace social media as a consumer engagement tool. He cites an example of hoteliers griping about Tripadvisor exposing service failures at their respective establishments. Parmet advised these service providers to embrace the brutal feedback, make the required changes (if valid), and then openly engage these “gripers” in the Tripadvisor forum. Nine times out of ten, he says, consumers will respect these efforts and turn into brand evangelists.

Real estate firms can use these same strategies to promote their brands, particularly around luxury or otherwise unique properties or locations, as well as their unique service value propositions. This said, why don’t real estate firms do the same as Tripadvisor? Homthinking, of course, already does this. But what if a real estate firm allowed consumers to openly rank its own agents. Not only would this be a PR-worthy event, but it would certainly elevate the service level of the agent base within the firm.

 How many agents would leave the firm because of this? Who knows. A more interesting question is how many would stay with the firm? Likely those who are confident in their own abilities, knowledge, and skills; basically, the weak flee while the strong remain. Who ultimately wins? The consumer. And if the consumer wins, chances are high that the consumer’s loyalty will remain with the firm that has the most transparency and the strongest agents.

Sourcing Web 2.0 customers, serving existing customers

By using Facebook, an agent could create their own Web 2.0 brand while controlling their sphere of influence and network. Real Living has already established this platform for it’s agents (or was it an agent, or group of agents, establishing this platform Real Living?). What a great way to kick start the engagement process while giving agents the ability to serve existing customers and find new customers (particularly echo boomers).

Gatineau Project marketing metrics

Eric Peterson continues to provide great insight. He has an exclusive profile of the Microsoft Gatineau project. At first glance, the Gatineau project is quite impressive. What’s particularly pleasing is that it appears to have been designed for marketing personnel and business managers. The visual representation of the data clearly indicates relevant campaign success and failure metrics.

Nevertheless, there are some considerations: Will this service give an accurate, and full representation, of data across multiple universes, or is it just limited to the MSN universe? Can firms track their competitors with this program? And with respect to their demographic data, it seems to be self-reported data from MSN, rather than from a wider sample data set; thus, how representative is the demographic data in Gatineau?

False profiles and the Internet consumer

Arguably, nothing messes with a firm’s loyalty and/or CRM strategy more than a multitude of false consumer profiles polluting a CRM database. In seeking to elevate one’s marketing engagement index, it’s often helpful to understand the demographic profile of a consumer. But if such a consumer does not self-report this, or if such data is not inferred, then firms are at the mercy of the garbage.

Interestingly, a research team claims in their research paper

The profiles users may contain fake information. We believe that our proposed algorithm can be used to identify and refine the profiles which contain bogus demographic information.

Essentially, this team analyzed web log files for search patterns and used an algorithm to predict gender or age. They claim a lift in accuracy of 30.4% on gender prediction and 50.3% on age prediction over traditional methodologies.

What makes this exciting is that, assuming futher testing bears out the team’s claims, companies like HitWise or WebTrends can incorporate this algorithm into its search pattern analsysis products. Firms can then use this core demographic information to craft more relevant landing pages, calls to actions, etc, on their websites.

Local market insight, marketing muscle

Where is the real estate industry on this chart? In terms of brokerages, arguably it’s between 2005 and 2006. Many real estate firms still encourage their agents to pursue off-line sphere of influence strategies (i.e., volunteer at the local charity, pass the business card around, wait for the call, etc) without a similar focus on Internet strategies. Indeed, many of these same firms are extremely uncomfortable with encouraging their agents to contribute to blogs, community forums, etc, due to fear that an agent will say something inappropriate, or whatever. And forget about these firms providing a company-funded blog platform for its agents!

Unfortunately, these risk averse attitudes drive marketing myosis.

What is social media? Wikipedia has a good answer. Why does social media matter? For the real estate industry it matters because the whole business of selling real is about engagement. And social media, at it’s core, is about engaging consumers immediately. Real estate firms who do not invest in social media devices aimed at engaging consumers directly or reinforcing the firms’ local expertise are at risk of sliding into irrelevancy.

What’s one of the easiest ways to begin the conversion? A corporate blog that is owned by the firm but also owned by the agents (in terms of content contributions). Why does this matter? This lets the firm’s agents demonstrate their local knowledge, superior marketing accumen, and reinforce their superior service value proposition. Why does this matter? Because consumers are going to “test” the firm’s claims by searching for validation of these claims. What better way to validate a firm’s deep local knowledge than to have an archive of such in a blog?

What’s an example of a great corporate-sponsored blog in real estate? This blog clearly demonstrates the firm’s local expertise, market knowledge, and marketing acumen, while giving its agents a platform to shine.

Swarm business / swarm creativity in real estate

Create value for the swarm. That is the overarching goal of a swarm business mindset. Swarm creativity embodies the passion that drives this goal, along with coolhunting as an adjunct exercise. Real estate, as an industry, seems well-poised to take advantage of swarm creativity.

Nicholas G. Carr, of the explains the basics of swarm business:

To achieve this status, a swarm-business aspirant must follow three principles. First it must “gain power by giving it away”. For instance the MySpace social-networking site works by granting its users the ability to determine its rules and content. Second, the company must be seen to “share with the swarm”—IBM, for example, has backed Linux’s open-source software with cash and code. Finally, firms must “concentrate on the swarm, not on making money”.

HBS Working Knowledge elaborates on swarm creativity:

There are five essential elements to collaborative innovation networks: learning networks, sound ethical principles, trust and self-organization, making knowledge accessible to everyone, and internal honesty and transparency.

Following Carr’s lead, a real estate firm must first abandon its possessive brand centrality and opt for a more decentralized brand presence. This means consumers, employees, real estate agents, vendors, and management equally “own” the brand. This means, at the core, a firm must open itself up to transparency and honest consumer review; which really means consumer ratings of its website, agents, customer service and then using these ratings as forums–conduits–to engage these consumers as collaborative partners to create a better value proposition. Internally, a firm could create a collaborative swarm between agents, IT, marketing, and management to build on the collaborative concepts derived from the consumer-based swarm insights.

For ROI-minded owners and managers, a swarm exercise is likely a hard pill to swallow, let alone ever digest. This is because swarm creativity lends itself to indirect monetization strategies (as does most social media). This could also be related to the fact that real estate as an industry, at first glance, is not really engaged in new product development processes (swarm creativity naturally lends itself to new product development ideation).

What is the real estate product? A house. What is the service? Representing a buyer or seller while giving advice.

This description is a bit facetious, but the point is that real estate professionals should begin looking at their entire web presence–and service value proposition–as an ongoing product that constantly requires new strategies and ideas that evolves in line with consumer expectations. If 10 swarm exercises yield one new service enhancement strategy that increases customer loyalty and retention, arguably the swarm exercise is worth it; especially if this strategy enhances a full-service agent’s consumer value proposition. In this example, ROI would be indirectly realized: as consumer satisfication increases, referals increase, and competitors suffer a corresponding competitive disadvantage (assuming they are late adopters). By implementing a consumer swarm idea, a firm has rewarded the swarm: first by listening and second by acting on its advice. This, in turn, promotes further honesty and integrity within the swarm and, hopefully, within the firm itself; eventually driving higher ROI over the long-term as internal strategies become integrally aligned with near real-time consumer driven initiatives.

Direct / social media marketing research 9.04.2007

Below is some fairly recent research on motivating and behavior factors underlying social networks. The theme of this set of research is to explore how the “echo boomer” or “millennial” generation uses social media. Since real estate is an engagement-oriented Internet based service, firms should study the motivations underlying their potential recruits and future customers to ensure they are well-positioned to serve them in the future.

Applying Common Identity and Bond Theory to Design of Online Communities

Mobile Text Messaging and Connectedness within Close Interpersonal Relationships

Leveraging Social Networks To Motivate Individuals to Reduce their Ecological Footprint (interesting analysis as to how a social structure nurtures affinity, loyalty, and evangelism).

Digital Relationships in the ‘MySpace’ Generation: Results From a Qualitative Study

Ceating an engagement index for real estate websites

As an increasing number of real estate firms seek to embrace and integrate Web 2.0 principles in to their websites, many of these firms may encounter a sense of frustration in having to “upgrade” once again to meet, or exceed, customer expectations regarding Internet-based services. Is real estate an Internet based service? Absolutely. With over 70% of real estate searches beginning on the Internet, real estate is decidedly an Internet-based services industry. But what kind of Internet-based services industry?

Rather than an “execute on what I already know” process, real estate is more weighted to a “search and gather” process. Few customers, in one search session, find a home, contact an agent, book a showing, and buy a house the next day. The majority of consumers spend several months, on average, searching for homes, viewing listings, compiling research, and saving preferred property listings before even registering with a firm or contacting an agent (i.e., searching and gathering). And real estate firms have tried to facilitate this search and gather process with their registration systems, drip marketing services, and online appointment making processes. But these tools align more with the “execute on what I already know” (i.e., utilitarian) aspect of the home search process; that is, these elements do not really help a customer determine what attributes to search for in home or community.

So, what should firms do to engage customers earlier and mid-way through the process to facilitate a higher degree of interaction with, and reliance on, the firm’s website to help a consumer define attributes? One way to begin is to set key performance indicators and develop an engagement index.

Creating an engagement index is a great way to assess overall site responsiveness to consumers’ search needs. Eric T. Peterson defines engagement as

Engagement is an estimate of the degree and depth of visitor interaction on the site against a clearly defined set of goals.

He has written a great series of posts on this topic. Part V of his series steps readers through the application of his process. Jeremiah Owyang adds some additional considerations here and here. And this blog actually walks through how to calculate “influence”.

Although these concepts in analytics may seem arcane, by focusing on such, real estate firms can begin the process of smoothly, logically, and economically moving their sites into the realm of Web 2.0. In future posts, I will explore how real estate firms may begin to create and apply an engagement index, and what elements they should focus on measuring regarding such.

Direct / social media marketing research 8.28.2007

McKinsey Web2.0 survey

Visual analysis of blog content

Web site semantic analysis

Emperical basis for social networks

Identifying brand influencers in social networks

Impact of trust in social networks

Target marketing in social networks

Correlation between LinkedIn and Facebook

Correlation between LinkedIn and Gmail, YahooMail, and HotMail

Real estate technology adoption principles

In 2004, Inman News profiled e-mortgage processes. In the ensuing years, paperless mortgage processes have improved but have yet to achieve wide agent adoption rates, as do many other real estate technology initiatives (e.g., real estate ecommerce centers). Could this be a classic example of the Technology Acceptance Model theories at work? ( Wiki definition 1, Wiki definition 2, research paper).

Many real estate firms have invested thousands, if not hundreds of thousands of dollars, in improving their technology offerings for their agents, only to see these technology investments gather dust as seasoned agents largely ignore–or at least fail to take full advantage of–such offerings in favor of their offline processes. The TAM predicts that a user’s perceived value of a technology resource affects this user’s adoption of this technology.

Assume that a brokerage wants to increase Internet ecommerce center participation and satisfaction rate amongst its agent base. This strategy makes good sense, as most real estate consumers begin their searches online, prefer the Internet experience, and eventually work with a real estate agent.

At its base level, a real estate ecommerce center answers mundane questions, finds out where a consumer is in the buying process, helps the consumer sift through much of the generic real estate information, helps the consumer refine search criteria, and then refers this consumer to a real estate agent. At this point, many brokerages would assume it’s the agent’s business to lose. But is it?

Many agents understand this basic qualification service. And this is where these types of services generally stop…basic. In other words, agents still are doing much of the work with an Internet client, in terms of driving towards a conversion, after this consumer is “handed off” to them. Yet from a brokerage’s perspective it’s doing a great service to its real estate agents by funding, staffing, and managing such a service. As such, there is a mutual perceived lack of usefulness on both parties (the agent thinking it’s less useful than it is, the brokerage thinking it’s more useful than it is).

From the standpoint of the agent, perceived usefulness would likely increase if the brokerage did more qualitative analysis prior to a hand off. For example, at varying points in the qualification process, call center personnel can round-out a client’s profile by either entering in data as they converse with a client, or refer clients to online tools that allow them to provide additional profile information. This data would extend beyond such basics as purchase time-line, preferred home type, newsletter selections, etc, and delve into lifestyle, preferred community attributes, etc.

Additionally, a brokerage could append basic demographic data to its pre-transaction consumer file by either using a reverse append service (Experian and Acxiom offer reverse append services that can attach a postal address to a valid email address) or by keying off the postal address the consumer registered with; regardless as to how a postal address is sourced, a brokerage would then be able to overlay zip code-derived lifestyle / life-stage and other demographic data. This would then allow consumers to choose home-types based on lifestyle (the brokerage’s listings database having been similarly overlaid with lifestyle / life-stage data, which enables this type of matching to occur).

These types of fundamental direct marketing techniques drive towards one goal: to hand the real estate agent a consumer who is well-informed and ready to act. Since the brokerage has tracked all phases of the communication leading up to a hand-off, the brokerage can deliver a profile-based client dossier to the agent who can then take this information and better perform his/her roll as a real estate trusted advisor (i.e., the agent can initially engage the consumer with a knowledge and insight gained as if he/she had actually interviewed the client in depth). Thus, the real estate agent focuses on his/her core competency, which in turn reinforces the usefulness of the brokerage’s ecommerce initiatives and further lowers barriers to adoption.

Profiling hedonic data in social networks

Continuing the discussion from the McKinsey interview of Cammie Dunaway, she states

[Yahoo!] is using behavioral data–really mining the wealth of transactional data we have about how people are spending their time online and trying to marry that data with attitudinal data…that’s where the most powerful insights can really come from.

Insights into what? It could be many things. Two of the most studied motivational data elements are utilitarian motivations and hedonic motivations. Utilitarian motivations center around goal-oriented behavior (e.g., I logged in to check my email, I checked my email, I logged out). Hedonic motivations are more social in nature (e.g,. I logged in to explore, to analyze, to decide, to eventually take action).

In real estate search, companies have typically focused on rewarding utilitarian behavior, often in a very reactionary manner. Consumer searches site > Consumer registers > Consumer selects home > Consumer is “passed off” to a real estate agent. Of course, the ultimate goal is to consummate a sale. And improving the “experience” of looking for a home on a real estate firm’s website could actually lead to more loyalty, referrals, and sales.

Nevertheless, overly focusing on “experience” at the expense of a goal can scuttle both consumer loyalty and ROI. Thus, balance lies in properly testing and deploying Web 2.0 assets that fulfill consumer goals while logically jibing with the product subject matter.

So how does mining attitudinal data fit this balanced approach or paradigm? Incenting consumers to add profile information that logically fits a goal is one idea. For example, if a real estate firm’s goal was to create a social network on their site targeted at tapping a suburban soccer mom demographic looking to buy a home, logical profile information may be zip code (current residence and desired residence), schools, sports, design preferences, and home type.

Zip code is important because the firm could relate this consumer to an agent who serves that zip code, where the agent serves as the social network ombudsman(woman) to answer questions and otherwise kick-start the group. Secondly, once a firm understands home type preferences and desired location, the firm can relate specific home information, community information and statistics, and other moms in the network to this person. The additional profile information constitutes community building information (e.g., relating moms who have children in similar sports). These steps help build a community and take the burden off the real estate firm to be all things to all consumers (if a mom has questions about how her child can join a traveling baseball team, she could ask the real estate agent, but more likely she’d ask the community). This way the firm’s “social asset” reinforces the firm’s local expertise, which allows for an eventual monetization of this consumer as she “graduates” through the process into ultimately looking at home types and eventually purchasing a home.

Through the tracking of profile data combined with the interaction of the consumer with the group (communications, postings, etc) combined with accessing utilities (e.g., widget downloads pertaining to design elements, video home tours, community data, statistics, etc), a firm could create an “engagement” index to validate whether their site is properly satiating consumers’ needs (Circuit City does this). The experience of this for the consumer is not so much having real estate listings and drip marketing pushed her way, but related data presented in a way that allows her to more deeply engage in the process and begin building a community before actually living in a community. Finally, in terms life-time value, this type of a social network could operate as a forum for a firm–and its real estate agents–to cultivate a valid and meaningful long-term relationship with consumers after they have actually bought a home (thus, closing the circle by adding transactional data with previously compiled attitudinal data).

Engagement marketing, using social media in real estate

According to McKinsey, global companies are increasingly using Web 2.0 technologies to engage their customers. Tapping web services, collective intelligence systems, and peer-to-peer network capabilities were the top three technologies companies were currently deploying or planning to deploy. Respondents indicated that customer acquisition was the number one reason they were deploying social media (the respondents also stated that they use Web 2.o media to more efficiently engage partners and suppliers as well as internal collaborative purposes). Several respondents indicated that social media is particularly valuable in terms of ideation and creation of future products.

In a similar report, McKinsey interviews Cammie Dunaway. Ms. Dunaway indicates that Yahoo’s concept of digital salons (online focus groups) have delivered unprecedented success with respect to new product prototypes and new product development initiatives. Yahoo also measures consumer engagement as a success metric (i.e., share of time spent on Yahoo and the number of media properties “consumed” during this time).

Applying social media to real estate home search is a logical step. Real estate firms should begin experimenting with new forms of engagement. Despite the fact that homes are not commodities novel opportunities exist to deploy social media. Virtual renderings of homes (pictures, virtual tours, etc) offer a rich bed of experimentation and engagement opportunities, and there currently exists technology real estate firms can deploy to support this initiative. For example, Benjamin Moore has a tool where consumers can select templates or upload pictures of their own homes and then change color schemes; Halstead Property has deployed a similar tool. There are 3-D home design platforms available.

 A creative firm could move beyond the virtual tour and allow consumers to actually change the color and layout of a prospective home; or grab widgets that have predefined parameters pertaining to build-outs or additions, thereby allowing consumers to visualize how a home would appear after the completion of such. Rounding out the experience, a firm could allow an agent, or team of agents, to answer questions via live chat and have a local interior design consultants “on call” to do the same. These types of consumer-facing features not only meet the consumer engagement parameters explored by McKinsey, but actually allows consumers to design or alter a product so they can visualize, experience, and “feel” how a home will look after purchase (allowing a consumer to virtually move in to the home and get a deeper sense of the living space). As Mini Cooper and Scion have found, the higher consumer engagement, the higher the return on customer acquisition strategies (measured in engagement and brand loyalty).

Semantic web analytics

Social media has created a challenge for website brand / product managers. Where social media is a rich fount of ideas, product information (negative and positive), etc, website brand / product managers have a challenge in using web analytics from these sources to drive site optimization (in terms of user experience, performance, etc).

Two recent research papers shed some light in the cave in terms of mining Web content. Imagine putting your hand in the Yangtze River and trying to catch a sturgeon minnow between two and three inches long. This is akin to conducting a simple keyword search and then singularly perusing each result to discern relevancy (one’s mind conducting semantic correlations to net down relevant results). The challenge is to derive a tool that drives the “semantic sifting” process higher up in the process, thereby making it more efficient to find relevant results.

Jean-Pierre Norguet, et al, discuss semantic analysis of website usage and how to apply this analysis to on-going website development. Nortguet’s approach combined web server log files, site content records, content calls by browsers, and TCP/IP packets. The Norguet team then ran these through an ontology-based OLAP tool. What it derived was a visual representation of interest values pertaining to certain categories of content. This visual representation demonstrated that despite a category’s breadth of presence across a website, interest value indicators provide valuable insight into consumer use patterns. Nouguet argues that visually displaying interest values allows for intuitive decision-making, which aligns more accurately with mapping and responding to consumer interests.

Michelle L. Gregory et al, explored a framework that allows users to map blog entries, query results sets, understand themes, and see how blog content changes over time. Gregory modified a tool called IN-SPIRE–which uses semantic indexing, among other things, to categorize result sets–to analyze 7,000 blog entries chosen at random. In addition to the powerful filtering and querying aspect explored, Gregory demonstrated how one can use this tool to build multi-lingual analyses using one’s native language. The team also delved into the realm of affect analysis. What they showed was powerful visual representation of positive versus negative feelings about a particular blog topic (taking the pulse of a slice of the blogosphere on a particular topic).

Some immediate applications of these types of analyses–in one’s native languge or across a multi-lingual website–are in improving web product development, mapping political sentiments, or sentiments pertaining to one’s own or a competitor’s product.

Trust indicators in social network marketing

Jeremiah Owyang explains the concepts and value of social networks from a marketing perspective in an easily digestible manner. Yang et al (registration required), Battiston et al, and Hill et al discuss the scientific underpinnings of these topics. Juxtaposing these discussions against one another leads to some interesting insights with respect to social media marketing.

Yang notes that in 1967, Stanley Milgram demonstrated that mutual acquaintances drive social network strength. As Yang elaborates:

“[T]he probability that two of someone’s friends know one another is much greater than than the probability that two people chosen randomly from the population know one another.”

Yang illustrates the concept of this theory by pointing to the success of Hotmail, which grew from 0 to 12 million users in 18 months.

Battiston explores how “trust” factors between actors in a social network affect the dynamics of recommendations in that social network.

“Trust plays a crucial role in the functioning of such socio-economic networks, not only by supporting the security of contracts [sic?] between agents, but also because agents rely on the expertise of other trusted agents in their decision-making.”

What Battiston drives towards is that trust-based modes of recommendation have an inverse relationship to traditional modes of recommendation, which are primarily based on the volume of recommendations as opposed to the value of recommendations. Battiston argues that trust-based (or value-based) recommendations are inherently better at promoting more satisfying results to actors within a social network.

This, in turn, promotes the propogation of sub-group cultures to form within the social network. And as non-trustworthy agents drop out of the network (because prior recommendations did not fulfill specific trust elements as dictated by the requesting actor), the sub-group refines itself overtime. As more sub-groups are defined within a social network, “network neighbors” emerge amongst members of these sub-groups, where these network neighbors operate as conduits between different sub-groups.

Yang demonstrates that sub-group performance, in terms of marketing results, out-performs all others (this was measured in terms of traditional transaction response rate metrics).

Accordingly, marketers must seek out sub-group network neighbors. These individuals are the brand influencers and advocates within a social network. Jerimiah Owyang has an excellent post on the visual display of this information. Leverage Software has developed a product which likely can visually display these sub-group cross-over individuals, thus making the selection of influencers and advocates easier. Perhaps these individuals would be great focus group candidates, “real time” collaborators in product development initiatives, etc?

Mining social network relationships

HitWise has demonstrated a correlation between LinkedIn and Gmail, YahooMail, and Hotmail and a corrleation between LinkedIn and Facebook. Hypothetically now…assume that LinkedIn and Facebook and Gmail, or YahooMail, or Hotmail share their databases, where a user’s email account address is the unique identifier. At this point it’s a matter of relational database mechanics to ascertain unique marketing–i.e., direct response, email, branding, etc–opportunities that these companies can exploit. What they (marketers, Facebook, Yahoo, etc) would likely look for would be “network neighbor” influencers (more on this in forthcoming posts).

Social Network Advertising

eMarketer predicts that in 2007 advertisers will spend $900 billion on social network advertising. As a real estate professional witnessing an explosion in social network sites (e.g., Active Rain, TruliaVoices) aimed at agents (and consumers), what are some first steps to engage this form of real estate marketing?

Step 1: Just understanding it. In this regard experience is the best instructor. Start by creating a LinkedIn profile and then get immersed in Active Rain or Trulia Voices, as voyeurs or members. These venues offer rich playing grounds.

Step 2: Find a blogger who’s singular passion is dissecting the process. As an emerging medium, early adopters keep the bog well-irrigated with creative ideas, foutainhead-like musings, and general full-throttled reasearch. Martin Reed does a great job at this. Of particular usefulness to understanding core concepts are his posts on basic concepts and resources and his monthly top posts page (valuable given it’s stream-of-consciousness threads). Another great resource is Matthew Sherborne. Follow his twitter marketing campaign journey to gain a blow-by-blow analysis and learn from the way he parses the process. Finally, Tranparent Real Estate has very cogently and concisely explained Web 2.0, and its relevancy to real estate professionals. The first post details the core concepts; the second post argues, in part, that social networks will fuel a collective intelligence that will apply pressure on professions to justify the value of their expertise.

ROI Conversations at Inman Connect

Notes from my presentation on ROI at the recent Inman Real Estate Connect conference:

Issue: What are the first steps real estate firms should take to get a handle on their data to enhance near-term and long-term ROI on this data?

  1. Since 80%+ of all originating real estate transactions begin on the Internet, firms should consider utilizing proven Internet analytics engines;
  2. Firms should create an existing consumer data warehouse that accepts data from whatever format and whatever source, normalizes this data, hygiene this data, to net down to a single record per consumer data set;
  3. Firms then should segment this data, overlay this data (e.g., with demographic or lifestage data), score and profile this data, and then model this data; this gives firms insight into their existing consumer data;
  4. This data warehouse then is used to drive marketing decisions pertaining to existing and emerging or new consumers.

VisiStat is a program to understand broad as well as locally-specific Internet use traffic that real estate firms can employ to make more informed decisions about how to manage their Internet resources, agent base, franchise locations, etc. The same can be said for Google Analytics, HitWise, etc.

But if we’re really focused on ROI, the key is consumer-specific data and the analysis of such. Accordingly, if one only looks at Internet based, or Internet derived traffic, it’s largely like looking at the top crust of an apple pie…the filling is where the substance is. And in the case of ROI that substance is a carefully constructed marketing database and marketing data warehouse where each consumer data record has been individually segmented, scored, and overlaid with demographic, psychographic, and lifestage data.

Hostage Marketing

I just finished watching the Bourne Ultimatum. Prior to the movie starting several hundred of “us” “consumers” were bombarded with advertisement after advertisement–most still, some animated, some filmed. We certainly were a captive audience. But many of us certainly were not engaged. This type of marketing is the epitome of hostage marketing.

I distinctly remember one advertisement, which was for Bionic Woman, a forthcoming NBC television show. Was I creeped out a bit being forced to watch the ad? You bet. Arguably, I guess I could have left the theatre for some popcorn; but then I’d have lost my awesome seat.

Thus, I was a hostage.

And my brand-affinity for this new show is tagged to the open-your-mouth-while-I-force-feed-this-message-down-your-throat-so-you-WILL-digest-this-and-visit-me-in-the-fall experience. Although I’ve always wanted to visit Stockholm, I don’t think I’ll make any loving imprints on this show.

Kula Rifting

What does the recent market success of Guitar Hero have to do with innovative concepts in real estate marketing? Activision, the third-party publisher of Guitar Hero, recently dethroned Electronic Arts. Activision’s market-leading success is due, in part, because it created a social object in Guitar Hero.

Attendees at the 2007 Connect conference will recall Hugh MacLeod‘s Kula ring presentation on the importance of creating social objects as Web 2.0 marketing message and community-building catalysts. Participating–and succeeding–in a Guitar Hero rift-fest is the Kula ring equivalent of returning with a shell necklace or armband–it’s the journey and the exchange of objects steeped in deep social value that makes the attainment of the goal important. It’s more process than product. And in the case of Guitar Hero, it’s not the plastic guitar that conveys “social status,” it’s the attainment of mythical rock god equanimity. The rift is the social object.

Much of Internet real estate marketing, past and present, seems to focus on driving mouse clicks (click the home attributes and price selections, click “Go”) and screen staring (waiting for the search results to appear). It’s a rather passive / reactive activity. Web 2.0 Internet marketing aims to promote social experiences. Consumers want to interact. Want to “touch”–virtually and non-virtually–the object of their home search. Consumers crave a process that’s meaningful and engaging.

What is the Guitar Hero equivalent in Internet real estate marketing? Is it a website where consumers can re-arrange the furniture, change the color, visualize an addition or build-out, etc, of their prospective home purchase? Is it a website where people compete in redesign concepts for another consumer’s recent home purchase? Is it a website that promotes social networking and viral marketing for a “meet up” at a home, rather than just a “showing”? Each of these websites could be one step on the journey, the process, of consumers’ home buying experiences that result in the ultimate goal–home ownership.

Real estate Kula is only a couple of rifts away.