September 9, 2022

Elevating Data: Elevators & Lead Gen?

Trei (our Robot Training Academy coordinator) is off to Cancun, a fitting rest given his excellent work with the RTA this Summer.  And it’s during his birthday, so we can’t send his gift for opening in real-time as we do for everyone now that we’re a remote team. Which means, we’ll send a gift to his apartment and hope it’s safe ‘til his return. No pity, he’s in Cancun! But this does make me think about elevators. 

So what exactly does an elevator have to do with package delivery and lead gen? 

Turns out, a lot.  But maybe not quite in the way you think it does. 

Boxing Day 

Envision the daily flow of parcels to an apartment building. How many come in? Well, if you’re an average large apartment building in the US, about 35 packages a day.  

(36M daily packages1 x 12.5% apartment dwellers2 = 4.5M packages x 50% living in large buildings = 2.25M packages in large buildings / 59K large apartment buildings3 = 38 packages per building, rounded to 35 as I’m cautious.) 

And that’s on a regular day. Think Christmas or even September 9, the most popular birth date in the US4, and you’re overloaded with parcels. On my home doorstep, maybe not such a big problem. But in a lobby, mailroom, or guard desk at your average tall building, it’s a growing pile of a concern. 

Someone needs to find a place to store these boxes until the owners come home from work, school, or even Cancun. And where do they go? Maybe in an oversized cardboard Jenga tower behind the desk. Maybe stacked precariously on top of the mailboxes in the mailroom. Or more recently, just maybe in one of those fancy new parcel lockers we find popping up in forward-thinking lobbies and sometimes outside the convenience store around the corner. 

A typical parcel locker. 

The concept of the locker is simple: the delivery service places the parcel in the locker and puts the key in your mailbox. Or they text you the combination on the “smart locker” version. You arrive home, pick up the package and drop the key off in the slot for the next use by your neighbor. What’s not to love here?   

So why not get one of these great lockers in your building? I mean, just have the delivery service install one, right? 

Not so easy – first, you’re presuming the building WANTS this capability installed. Depending on the model, it’s bulky and functional-yet-less-pleasing to the eye. Then, the building would have to decide which service to work with. Do you go with the National Postal Service? Or maybe the all-digital e-commerce giant? A private third party?   

Getting the real estate of the last-mile with your name on it is a long-term win for any delivery service. Since the delivery services have the most to gain from locker placement, they’re the ones who need to sell their way into these buildings. With meaningful leads!

But where to get this information?   

Let’s unpack this problem, shall we? 

It seems simple: just speak with the person who makes the decision on installation of parcel boxes within a high-rise. Is it the Building Owner? The Property Developer? Maybe it’s the Property Manager, or the largest tenant of a mixed-use commercial building. How about a Homeowners or Condo association, might they have a voice in this issue? 

Underlying each of these great questions: how do you find the right contacts to hear the message? 

This was the request put to us by a national delivery organization in Canada. Having just finished our third year of providing AI-driven lead gen to this organization -- and helping them absolutely crush their install quotas -- we’ve learned several things about the curious data needed to sell into large residential and commercial buildings. 

What goes into the decision making process for this – is it lobby esthetics? Finding space for it? The presence of a doorman or an attended mailroom? The notion of a gatekeeper and influencer also comes into play here. All the more reason to get even more contacts. If you can build a map of the players within an enterprise, you’ll be able to ascend to the decisionmaker and close the deal. 

This is lead-generation on steroids, and honestly one of the more rewarding projects we’ve worked on. It required us to use all the tools in our arsenal and resulted in the development of several new ones. 

Let’s look at all the curious places we searched to find that elusive “best contact”.  Each of these had some importance to the problem, and we looked at them all (always legally, see What Data am I Allowed to Use?).  In the end, the more data you have the more likely it is that you’ll find the solution. 

Ground floor: raw data 

For this project, we started with an underperforming marketing list of buildings from the client, and property management listings pulled by NAICS.  It just wasn’t fitting together – the customer used a call center for level one, a second-level force for warm leads, and a rainmaker to bring in the multi-building enterprises through relationships. But the level one calls were just not delivering, so few significant leads were making it to level two. The data was old, or the wrong contact, or the wrong management company. 

So we fired up our data gathering engines and looked at: 

  • Direct Property Data Gathering: Real Estate, Apartment Rental, and Property Listing Websites are great places to find information on buildings and typically a phone number for information. This is a starting point to identify locations of interest and a potential lead for follow-up. 
  • Listing Services: Rental/Leasing Agent and Property Manager listings are great ways to triangulate to the potential manager of a building.   
  • Open Data Sources: In Canada, condo boards need to register with the province. In the US, these associations are non-profits that need to register with the IRS. In both cases, there are sources that can at least get you the link between the organization and the building. 
  • Search Engine Trickery: Leverage your favorite tools to explore the data available before buying anything.  You can do this yourself, at small scale. Learn to use the advanced search criteria available from Google or other engines to really juice your search capability. Once you’ve gotten good at searching queries like (“Hillcrest Terrace Apartments” AND “Property Manager” AND "St. Catharines" phone) you’ll want to automate it in… 
  • Paid API’s: we like Google Places for business resolution and Bing Web Search API for keyword hints. Do note: we use these services to deliver pointer data that corroborates information we already have. Do your research on how to use paid API’s and what NOT to do with them (like, build databases from the raw results). 

Oftentimes, just getting the phone number is a giveaway – connect the number from one listing to a separate listing of Building Contact information, and you’ve made the elusive link.

This type of work is supported by our Advanced Business Data Graph, 100 million strong with companies around the world. Connecting the raw data to our curated data made all the difference in this project as we turned raw signals into actual business records. 

Fill that car and rise up 

Once we had the leads, we still needed to figure out an order of priority for execution at the call center.  Enter our segmentation strategy, using: 

  • Neighborhood Information: Demographics (trends about the people) and Firmographics (trends about the businesses in the building) were used to identify traits that can be used in the selling process. The average age of the tenants, or type of businesses located in mixed-use buildings, helped target the prospects more effectively. 
  • Proprietary Client and some Insurance Data: The client was able to deliver detailed information on past parcel deliveries to some locations. This information, correlated with Insurance data on the type of building (including esoteric things like fire ratings, age of structure, even building materials) were used to segment and classify the buildings into appropriate prospect lists. 
  • Business Cluster Graphs:  these are particularly useful in finding property management companies that operate multiple locations.  If you can sell one agency on the concept, it’s likely you’ll pick up several buildings. The client typically put the rainmaker on the largest of these companies, with good results. 
  • Dun and Bradstreet Marketing Data: Another important aspect to this project was the use of partner data to fill out the records. For this project, we used D&B data to provide both additional fields and fit within the customer’s current approaches using their products. When you can make it work, it’s always better to have more data to support the final customer output. We love working with D&B to complement the data projects we deliver, and our partnership with them helps enhance their core dataset, too.  

The round trip method 

With our leads and segmentation in hand, we tried these leads out with the call center.  And they worked! 

With small successes at first, we gained momentum. And arrived at a clear difference that should be part of any data project – testing and review and tuning. More important than the “wins” were the “fails” that we received back from the call center. This helped us tune the engines for better leads – leaning into the methods with the best traits and reducing the bad ones. 

Hearing back bi-weekly from the call center and client on what was working and what was failing was a great help to making our joint numbers and made all parties part of the same team. 

Note that we say “reducing” not “removing” bad records. At scale, there’s really no benefit to aspiring to the perfect list. What you’re looking for are reasons to continue on a path, or a heightened awareness that you may need to cut things early. And the true benefit of this constant feedback? You get a realistic sense on when you’ve exhausted things. If your Clean Rate is 90% and your Warm Lead Rate is 20%, you have a benchmark. Once you start reducing Warm Leads to 15%, you know it’s time to re-assess methods. When it hits 10%, you take a hard look at whether the campaign has run its course. 

Lift up the best one 

There’s usually no “one right source” when you’re dealing with a complex data question. If you could just buy a list of property decisionmakers and be done with it, you’d feel pretty good. Unfortunately, there are companies out there that will sell you that list, which almost always underperforms. That’s what our client did before engaging with us. Could it be that they got the shaft from their first source? Possibly. 

This process took time, and used probably 20 different angles to get to the best solution.  You might actually say we looked at this problem “sideways and slantways and longways and backways and squareways and frontways and any other ways you can think of.”  And that breadth of data investigation finally paid off in conversions.

But since we’re here, we’ll give our view on the best source for the gathering of current decisionmakers in a building. Would you believe – it's the certification and inspection process for elevators from Open Building Data

You’ve seen inspection certificates in any elevator you’ve ridden in (I hope!). That inspection is usually recent to 1 year, and authorized by a key decisionmaker for the building. You want to sell into a building? Find out which organization, and which leader, is responsible for the safety of their lifts. We found this gold-mine for Ontario at the Technical Standards and Safety Authority.

Back to the lobby exit 

So there you have it…an underperforming campaign turns on its head and finally rockets to success with the use of some curious data techniques.

Giving credit where due: our dear friend Steve M. first pointed us to the elevators dataset and asked, “can you do that”?  Why, yes we can, Steve. Once again, thanks for the tip. 

And Trei? Enjoy unboxing that gift when you return. Rest easy that you’ll soon have a parcel locker in your mailroom, we checked that address and the lead’s at the call center already. 

Bob 

CEO, rel8ed.to Analytics

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St. Catharines ON L2R 7E1


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