HousingWire ✓

@HousingWire · United States · joined 12 Nov 2008

HousingWire provides unique data and research, respected business journalism and must-attend events for housing leaders.

127 512Followers

72Following

61 036Posts total

8.9KViews on collected posts

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HousingWire ✓@HousingWire7 Sep

@HousingWire That’s the key divergence: inventory can rise while the best homes still move. In underwriting, broad market headlines matter less than submarket days-on-market, price cuts, taxes/insurance and the actual rent-to-payment spread. 9 views · 0 likes · 0 reposts · 0 replies Open on X →

HousingWire ✓@HousingWire7 Sep

AI can automate tasks and surface insights, but it can’t fix fragmented workflows, siloed data and systems that don’t talk to each other. Bonnie Chong of Moder argues that the bigger opportunity is redesigning the mortgage operating model around connected data, intelligent https:

0:11

1.7K views · 3 likes · 0 reposts · 1 replies Open on X →

HousingWire ✓@HousingWire7 Sep

Can tech keep agents out of trouble for listing mistakes? https://t.co/WxD13KOgt8 1.8K views · 1 likes · 0 reposts · 0 replies Open on X →

HousingWire ✓@HousingWire7 Sep

@HousingWire Orlando is not the widest split in Florida. On my own 9/3 read, Panama City Beach condos are off about 3.7% year over year at roughly 94 days on market, while 32459 is still closing near 95% of ask. Is Orlando softening in condos before single-family too? 37 views · 1 likes · 0 reposts · 1 replies Open on X →

HousingWire ✓@HousingWire7 Sep

Truss Financial scales hybrid model with new direct lending platform https://t.co/g4gbaEM799 1.7K views · 1 likes · 0 reposts · 0 replies Open on X →

HousingWire ✓@HousingWire7 Sep

Florida’s housing market looks shaky. Orlando tells a more complicated story https://t.co/8mZ8WoWFAx 2K views · 5 likes · 2 reposts · 2 replies Open on X →

HousingWire ✓@HousingWire7 Sep

https://t.co/2QvQntvpTF rolls out tech platform to streamline home purchase agreements https://t.co/stcPJvQEDt 1.7K views · 0 likes · 0 reposts · 0 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

7 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 100K–1M ผู้ติดตาม ต่ำกว่าบัญชีรุ่นเดียวกันทั้งการเข้าถึงและการมีส่วนร่วม.

ยอดดูมัธยฐาน1 664บัญชีนี้4 856ค่ามัธยฐานของ 100K–1M

การเข้าถึง, %1.30%บัญชีนี้1.80%ค่ามัธยฐานของ 100K–1M

การมีส่วนร่วม, %0.06%บัญชีนี้1.32%ค่ามัธยฐานของ 100K–1M

ตัวชี้วัด	บัญชีนี้	ค่ามัธยฐานของ 100K–1M	อัตราส่วน
ยอดดูมัธยฐานต่อโพสต์	1 664	4 856	0.34×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)	1.30%	1.80%	0.72×
อัตราการมีส่วนร่วม	0.06%	1.32%	0.04×

บัญชีอื่นในช่วงนี้ → เปรียบเทียบกับบัญชีอื่น → ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

1.7K7 Sep

1.7K

1.8K

1.7K

Last 7 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.00%7 Sep

0.50%

0.06%

5.41%

0.06%

0.24%

0.00%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.32%.

What the audience does

Likes55.0%11 in total

Reposts10.0%2 in total

Replies20.0%4 in total

Quotes5.0%1 in total

Bookmarks10.0%2 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

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เทียบกับบัญชีขนาดเดียวกัน

Growth & engagement

Views per post

Engagement rate per post

What the audience does

บัญชีที่คล้ายกัน