How do I keep on top of upcoming lease events and act on them before they become voids?
When you have voids coming up in your portfolio, it’s useful to have in mind that it always costs more money to attract new tenants than it does to retain existing ones.
It’s why most asset managers pride themselves on high occupancy rates across their portfolios. All the while there’s a tenant in place, the property is earning income.
When a tenant’s break option is coming up, you’ll likely already have a sense of whether or not they’re planning to exercise it. Before the end of their lease – you will have already applied a renewal probability to your business plan.
But what can you do to improve those odds?
BACK UP YOUR ASSUMPTIONS WITH DATA
It might go without saying for some, but backing up assumptions using rich data will always provide you with much more confidence when making business decisions.
Many asset management teams are still relying heavily on Excel to forecast their plans for the year ahead, and it’s common to export just a snapshot of data from a property management system and send it to an analyst to extract some form of insight from. Data is often then copied and pasted from Excel, via email and ultimately finds its way into a PowerPoint table.
This manual process is lengthy and exposed to many human errors, such as typos and cell formatting issues from using the copy and paste function too much. It also studies a minimal dataset that is often out of date by the time it’s viewed.
By combining all of your data sources, you gain a more holistic view of your portfolio. Using Coyote, you can view all of your tenancy data consolidated from any number of property management systems on a user-friendly dashboard that every team member can access remotely. Particularly useful when teams work across different regions.
This level of transparency doesn’t just help support your assumptions but can also unlock further income opportunities for more intelligent asset management.
Some events are entirely out of your control and, for the most part, inevitable. For example – if a tenant company was to go out of business instantaneously. There’s only one thing you can do in this instance, and that’s just to ensure you’re ready to react.
It’s unlikely an event like this would come entirely out of the blue, but often the murmurs are picked up verbally in tenant conversations and onsite meetings with your property managers.
Asset management teams use Coyote to log ALL of these conversations, and the account notes then sit alongside the rest of the information relating to the asset in question.
As a result, you can react to the unexpected with confidence and trust that you and your team are all on the same page.
START CAPTURING ALL OF YOUR DATA WITH COYOTE
DO THE RESEARCH
A section of Coyote, which many of our asset management clients find useful when handling lease events, is the Infabode integration – the industry-leading real estate research platform with more than 900 content providers.
When you look up an asset in Coyote, you see relevant market research and the latest industry news from Infabode, right there in the research panel of Coyote.
Combining contextually relevant market research from Infabode with live structured data and the narrative of relevant conversations adds just another level of trust to your day-to-day decision-making.
ADAPT WITH YOUR TENANT
If a tenant needs to downsize or relocate for lower rental payments, you might want to offer a rent-free period or month-to-month payments to help them get back on their feet. Perhaps you’d be willing to move them into a smaller unit elsewhere within your companies portfolio.
Others might grow exponentially and need more space way before the end of their lease. Do you have a larger unit becoming available in the next few months that you could move them into? You might want to offer them an early exit from their current lease and draw up a new one for a longer-term and at a more profitable rate.
I may start to sound like a broken record in saying this, but the solution is logging ALL of your data in a structured format. If your tenancy data is stored across disparate systems or lost in the ether of verbal conversations – it’s unlikely you’ll be able to gain much insight from it at all.
IDENTIFY NEW TENANTS EARLIER
When you have a tenant talking about leaving your property, it’s likely another landlord is having similar conversations with one of their tenants too. By efficiently tracking the leasing market in your sector or area of specialty, you may well be able to identify your next tenant way before any of your properties become vacant.
Asset managers receive an abundance of data that could help to identify a new tenant. You could receive it in several ways – an investment sales brochure containing a tenancy schedule, a text from one of your leasing agents, or perhaps a snippet of information overheard in a conversation between industry peers.
Either way, this is readily available, direct, and verified data – it’s just not in a structured format.
If you’d like to target tenants you think may be nearing the end of their lease – you need to know exactly who they are, the end date of their lease, their notice period, the amount they are paying per square foot. You need a full and deep dataset.
By logging all of this raw and unstructured data using Coyote, you can start to build a vast and detailed lease comps database for you and your team.
When the data is stored correctly, you can access actionable and detailed market intelligence of higher quality than ever before. It’s not anonymized; it’s not a partial data set. It’s complete, and it’s unique to your team – much more powerful.
Use your own lease comps data to identify potential new tenants earlier and get the conversations going before spending any money on marketing costs.
You are the expert in your sector, and the lifeline of your business is to understand your market.
Start logging ALL of your real estate data in a structured format using Coyote to gain a more profound and relevant understanding from it than ever before.
Make your existing data work for you.
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