Tim Martin: I’m not sure necessarily — it’s hard to predict the distress or at least the – seller motivation. I’m not sure that we have a house view on geographies where we would expect to see more seller motivation. I think it’s more unique to an individual situation and individual seller drivers be it whether it’s debt that’s maturing interest rate hedges that are burning off other liquidity needs. I’m not sure it’s a geographic driver as much as it’s to many, many other factors.
Steve Sakwa: Great. Thanks a lot. That’s it for me.
Chris Marr: Sure. Thank you, Steve.
Operator: Thank you. And your next question comes from the line of Keegan Carl from Wolfe Research. Please go ahead.
Keegan Carl: Yeah. Thanks for the time guys. I kind of hate to belabor the point on because I know we touched a lot on the magnitude, but just kind of curious where your thoughts are specifically on cadence? And then, how are you thinking about your two different buckets of customers, for example the longer-term customers versus those that have moved in say within the last year?
Chris Marr: Yeah. On the cadence, the overall process is dynamic for the existing customer, as it is with the new customer coming into the portfolio and that the system is going to get a lot of varying inputs, which would include amongst others, how you came into the portfolio, whether that’s paid search, whether that’s walking into the store, did you come in through mobile or did you come in through desktop? Did you call? How are you paying us? What form is that payment taking? Is it debit? Is it credit? Is it cash? When we think about the occupancy of the individual cube that you’re in both in that store in that submarket when we look at our forecast for rerenting that cube should you choose to vacate where do we see that demand coming from.
So there’s a variety of factors which then translates into a pretty dynamic sense of timing for those increases depending upon those factors. So it could be in that four to six month range, could be once a year it really does depend. So that’s been pretty evolutionary here over the last couple of years, as the systems and the machine learning keep getting smarter and smarter and providing us with more and more insights. I think as we look across the portfolio obviously, it’s going to depend upon the fundamental performance in those markets as one component. What’s going on with existing pricing in those markets where you have steeper changes between last year and this year in terms of asking rate for new customers that’s going to have an impact versus those more urban markets that have seen less steep change in price from last year to this year.
So yes, that’s kind of how we think about it.
Keegan Carl: Got it. And then shifting gears to occupancy. Just kind of curious where you expect your year-over-year occupancy delta versus last year to trend for the balance of the year?
Chris Marr: Yes, I think as Tim mentioned we were 130 down at the end of October 117 yesterday. So, think that number is going to be between that 120 basis points down from last year to 150 is likely the area that will end December.
Keegan Carl: Great. Thanks for the time guys.
Chris Marr: Thanks.
Operator: Thank you. Your next question comes from the line of Hong Zhang from JPMorgan. Please go ahead.
Hong Zhang: Hey guys. You’ve done a really good job at keeping personnel expenses low throughout this year. I was wondering if you could touch on what initiatives you’ve been doing to achieve that? And I guess for lack of better words how sustainable is that going forward?
