Smart Buildings: Unlocking the Value in People Analytics Data

The race is on.

Who can use Smart Building Data in the smartest ways?

We could struggle on our own, but there’s a mentor here to teach us.

Let’s not waste any more time.

A Bit of Background

Over the past few years, owners and managers of Smart Buildings have been on a highly competitive quest. The ultimate goal of this quest is to unlock the true value in the data that their newly equipped Smart Buildings now generate. Every hour, every minute, every second.

With mid-race results looking promising, we are now in search of the next level of value in this data — who will crack the case first?

This series of posts describes an optimistic attempt to crack this case, or at least, take an initial swing to chip away the rock. I do this by exploring the potential that lies in capturing best practices from the field of Website Optimization, and directly applying these practices to Smart Buildings. A dream-outcome would be to bring forth an entirely new discipline: Smart Building Optimization. But then, what is the link between websites and buildings?

The structure of a building can be compared to that of a website, where the spaces that form a building are similar to the pages that form a website.

The idea above is perhaps not completely new, but its real meaning and potential value have never been explored, described or put to use. Now that our buildings have become smart, we can precisely track the activity of the users of these buildings. This is exactly what software like Google Analytics has been doing for over a decade, but then for websites.

So why would we not take best practices from Website Optimization –a field that has matured over the past 13 years– and apply these to our young field of People Analytics for Smart Buildings? Smart Building Optimization.

This first post is designed to set the outlines for an initial taxonomy — or dictionary — that allows us to translate the language and methodology from Google Analytics for websites into one for People Analytics for smart buildings: buildings are websites, spaces are webpages, sensors are tracking codes, and so on.

In the posts that follow, I will use this taxonomy to transfer best practices from the web to real estate — with the purpose of creating the ultimate building instead of the ultimate website.

Buckle up for a deep-dive into the field of applied data analytics, conversion optimization for your Smart Building, and interviews with Website Optimization guru’s.

No prior Google Analytics knowledge required.

Identifying Similarities: Meet the Mentor and the Protégé

“If you cannot see where you are going, ask someone who has been there before.” - J. Loren Norris

In this section, I will briefly introduce user analytics for buildings (the Protégé) and user analytics for websites (the Mentor). Then, I will go into three shared traits that make the two so highly compatible.

The Protégé: User Analytics for Buildings

The field of People Analytics for Smart Buildings has progressed rapidly over the past few years. The main Applications up till now have been mainly focused on visualizing and tracking building occupancy, and user traffic. The Protégé shows large potential for the future.

Collecting data about user behavior in a building can take place through a variety of techniques. The most widely applied techniques are sensors, beacons, and WiFi-triangulation. Diving into the pros and cons of each of these methodologies, and how these translate to Smart Building Optimization, is a venture for another time.

After data is collected, it is transferred into a database. From this database, the data can be accessed and visualized through an interface. This visualization provides the building owner or manager with information about the past, present and future (predicted, based on historic data) status of their building. In case of People Analytics, these insights can include:

• The number of users inside the building.
• The utilization rate of spaces.
• The average time spent inside the building per user.
• The most popular walking routes.
• And so on.

Adoption is booming for the Applications described above for a variety of reasons, such as: leaner asset management, realizing cost reductions, improving user experience and supporting sustainability efforts. This rapid adoption has brought forth enormous sets of new data. Most of this data’s value however remains untapped. We need a mentor to teach us how to harness this value.

Meet the Mentor: User Analytics for Websites

So what does Websites Analytics do? Website Analytics software tracks a website user’s behavior, providing the website owner with highly detailed insights into the user’s behavior during his or her visit. This data collection and processing takes place in exactly the same way as it does in people analytics: the user’s behavior is tracked and collected, the data is transferred into a database and then visualized for the website owner.

Collecting data in this way provides the website owner with a variety of insights, such as:

• The number of users that visit their website.
• The duration of each viewed page per user.
• What content the user interacted with.
• Which browser the user uses.
• And much more.

Nowadays, having a website without Website Analytics software is almost unthinkable. Estimates (of already three years ago) are that 30 to 50 million websites use Google Analytics — this estimation does not take into account all other Website Analytics software providers.

Over the past 13 years, the field of User Analytics for websites has developed rapidly, and has proven to be successful in translating user information into value. Through Website Analytics, websites now significantly contribute to the goal of their businesses, whether this be boosting revenues, optimizing user experience or increasing traffic.

The Protégé and Mentor — Shared Traits

When going through the introductions of the Protégé and the Mentor, we can identify three traits that make the two highly compatible.

• First. The type of information that they collect. Both the Protégé and the Mentor are proficient data collectors of their users, and focus on the same type of data: the number of users that are in their domain (building or website), where these users come in, how long these users stay, what routes they take, etc.
• Second. The methodology through which they collect and process data. Both the Protégé and the Mentor collect data by tracking user behavior, then store it in a database, and finally visualize it for the owner of the data.
• Third. The way in which they can potentially create enormous value for their business. Webpage Analytics has generated billions and billions of euros in value already. The Mentor has proven its worth, the Protégé, however, still has a lot to learn here.

At this point, The First and the Second shared traits are in place for us. Now it’s up to us to use these two to bring forth the Third. To help us achieve this goal, we construct a taxonomy that allows us to translate best practices from Website Optimization to Smart Building Optimization.

Building Bridges — a Basic Taxonomy

“I just don’t like big guys who speak cryptically and act like they understand the language better than me.” - Robert Downey Jr.

In this section, you will find seven basic elements through which websites and buildings can be linked. There are many more however, with various levels of complexity. During the remainder of our adventure, we will continue to add to this taxonomy of shared language between Protégé and Mentor.

1. Our building is their website. The obvious one. We can view a user that visits a website in the same way as a user that visits our building. Whenever the user enters a website, they are tracked throughout their stay. The rise of People Analytics for Smart Buildings allows us to do the same within our domain.
2. Our spaces are their webpages. Buildings consist of a variety of spaces. Similarly, websites consist of a variety of webpages. Each space in a building is there for a reason — for example to provide the visitor with an entrance (which functions just like a website’s home page) or a reception area (which functions just like a website’s help page or search bar).
3. Our user actions are their clicks. Navigating a building is similar to navigating a website. Clicking a button that brings us to the next webpage is similar to opening a door that brings us to the next space. Clicking on a piece of content on a webpage is similar to interacting with objects or people within a given space.There are however many more actions that are tracked on a webpage, and that may also be valuable to track in our spaces. Website Optimization will show us where to look first.
4. Our sensors are their tracking codes. Okay, now we’re getting deeper into the subject matter, and things start to get interesting. Did you know that before Google Analytics can track website users, the website owner needs to install a small piece of Javascript code to every webpage? This is very similar to equipping building spaces with devices that collect data, such as sensors. Only after these sensors are installed, our building’s database will start being filled up with data from the use of the building.
5. Our building visits are their sessions. Google Analytics works with so-called sessions. Whenever a user ‘enters’ the website, the session starts. When the user leaves the website, or is inactive for 30 minutes, the session ends. Sessions are crucial for creating functions, reports and statistics.A visit to our building can be viewed as a session as well, and allowing 30 minutes of inactivity may be interesting to apply to Smart Building Optimization. When a user of our building leaves the building, this does not necessarily mean their actual visit has ended. Perhaps he or she is grabbing lunch outside or going for a smoke.
6. Our devices are their cookies. When a new user ‘enters’ a website for the first time, the website automatically installs a cookie on the user’s browser. This allows the website to identify a returning user, and to combine the data from their various sessions, leading to new insights.Smart Buildings can identify returning users through the unique addresses of the user’s devices. This identification process however is not as straight forward as for cookies, and has serious privacy implications (yep, GDPR). We’ll definitely come back to this sensitive subject at a later stage.
7. Our Visitor Journey is their User Flow. When a user enters a website, Google Analytics automatically tracks the route that the user takes. Did he or she directly go to the help page after entering the website? This is valuable information, since if this behavior comes up frequently, this could mean that the route that the website owner wants the user to take is unclear. For a building, this analysis can be valuable in a similar way. Do users frequently turn to the reception desk for directions upon entering the building, while you do not intend them to? Chances are your signing is off.

With the basic taxonomy in place to bridge the gap between the web and real estate, we are almost ready for the next step: identifying best practices and applying these to our field.

It’s All About Adding Value

“Don’t reinvent the wheel, just realign it.” - Anthony J. D’Angelo

Websites create value when these contribute to the goals of their business(es): to the selling of a product or service, to sharing information, and/or to creating exposure.

Real estate, in the same way, creates value when it contributes to our business goals: attracting employees to the office, inviting potential buyers into your store, or stimulating sustainable or social behavior.

Website Optimization is about getting the most value from a website. Smart Building Optimization could do exactly that for real estate. It will help us contribute to business goals, validate our assumptions, measure our performance, track our progress, and showcase our added value to the business.

A Flavor of What’s Coming

To give you a flavor of how value from Website Optimization could be applied to real estate, I introduce two concepts from Website Optimization, and show you what translating these to real estate could mean.

Bounce Rate

In Website Optimization, Bounce Rate refers to the percentage of users that ‘enter’ the website and then immediately leave the website. A high Bounce Rate could indicate that the website’s added value to the user is uninteresting or unclear.

Translated to real estate, Bounce Rate could mean that a user enters your store or your newly decorated office space, and then immediately leaves. How does a Website Optimizer decrease bounce rate, and what can we learn from that for our field?

Conversion

I expect conversion to be a core concept for Smart Buildings Optimization. From my brief exploration into Website Optimization, and my previous experience with developing digital products, it is all about conversion. Conversion on a website refers to the percentage of users that perform the action that you want them to take: click your product, buy your product, read your article, or share your content on social media.

For real estate, this could translate to the share of people that enter your store, try your product, and then purchase it. In an office environment this could be the share of users that use your newly designed workstations or meeting rooms. How do Website Optimizers boost conversion? And how can we apply this to real estate?

Up Next: a Conversation about Conversion

In my next post, I will put the theory presented above to a first test. I will do this by interviewing Website Optimization specialists. Can we translate their best practices to our field? What would their translated practices look like? And what value could these practices potentially add when applied to our field?

Before publishing this first post, I shared the draft version of it with a specialist in Website (Conversion) Optimization. He replied:

“Wow. This is nice. Let’s meet up and do some work on this. I already have a few ideas.”

We’re meeting this week.

Want to read on? In Part 2 of this series, I explore four principles that will help us create new value from our data.