Chancelle de Freitas moved to the UK from South Africa five years ago. After her baby arrived eight weeks early, it became an eye opener - life is short and anything can happen, so why stay still? That question led her to property. She still has a full-time job and a two-year-old at home, which means her property journey has moved at its own pace - but she is moving, consistently, using Property Filter to find motivated sellers in Solihull and Birmingham before anyone else picks up the phone.

Chancelle's challenge before Property Filter

Before Property Filter, Chancelle's process looked like most early investors: scrolling through Rightmove, trying to identify good deals from a standard listing page, and moving when something caught her eye. The problem was that by the time she moved, other people had already moved faster.

She describes the pattern clearly. She would find something that looked like a good deal - the kind of listing that makes you stop and think, is this too good to be true? After sitting with it for a moment and convincing herself it was real, she would phone the agent. The response was almost always the same: they had been inundated with inquiries and were not taking any more viewings.

"I found that it sped up me getting to the agent first versus me scrolling and scrolling and eventually finding a deal."

The cruel part was that these calls confirmed she had spotted something real. She was not misjudging the deals - she was just arriving too late to act on them. What she needed was not better deal-spotting instincts. She needed a way to know about motivated sellers before the rest of the market did.

A conversation at a networking event introduced her to Property Filter. She signed up for the 14-day trial and found it useful immediately - though she was honest that the first reaction, as with most new platforms, was that it felt overwhelming next to the Rightmove interface she was used to. For a while she was jumping between the two, until the pattern became clear: Property Filter was consistently getting her to agents first.

How Chancelle uses Property Filter to find deals in Solihull and Birmingham

Chancelle's approach in Property Filter focuses on two motivated seller signals: properties that have had their price reduced and properties that have sold and come back to market. Both signals suggest a change in the vendor's circumstances that might make them more open to a realistic offer. Neither is easily visible on a standard portal - you need property sourcing software that surfaces the pattern across the full market.

The practical difference she describes is in the conversations. Before Property Filter, her calls to agents were cold - she knew what the listing said and not much else. Now she is often one of the first callers on a motivated seller property, which changes how the conversation goes from the start.

"The fact that Property Filter already filters the motivated sellers for you without you having to do that, without having spreadsheets - definitely one of the biggest things is time."

Time is a genuine constraint for Chancelle. She still has a full-time job, and a two-year-old at home means her available hours for property work are limited and unpredictable. A platform that does the filtering for her - without requiring a spreadsheet to be maintained alongside it - removes a layer of manual work that would otherwise eat into the time she does have.

She uses Property Filter's pipeline to organise her tracked properties. Her tags are tied to strategy: short lease, assisted sale, title split. When she comes back to a property after a few days away, the tag tells her immediately why it is in her pipeline and what her thinking was. Her husband has also joined Property Filter, and they use separate named tags so they can each see which properties the other has added to their shared pipeline.

Alongside the tags, she uses the notes function religiously - writing down her thinking the moment she views a property, so it is there when she comes back before a viewing or after it. It is a small habit, but it keeps the pipeline usable rather than growing into a list of half-remembered properties with no context.