"Search engines today don't just respond to keywords - they use AI to anticipate intent. Viktoria explained how Google pulls from review sites like Avvo, legal directories like FindLaw, and even guest posts or media mentions to build a profile of your firm. When someone searches "New York personal injury attorney," Google factors in their location, recent searches like "slip and fall," and other user behavior to tailor results."
"Viktoria emphasized that the foundation of strong legal marketing starts with clarity. You need to define your ideal client - whether that's a high-net-worth individual approaching retirement or a newly pregnant couple planning for the future. You can have multiple profiles, but they must be specific. Once you know exactly who you're trying to reach, your messaging and targeting become far more effective. Without this level of focus, marketing becomes diluted and inefficient."
"Vet Vendors Who Know Your World Legal marketing is an unregulated space, and Viktoria didn't hold back in expressing her frustration with how many lawyers get burned by bad vendors. Her advice? Ask agencies for references from clients just like you, same practice area, same marketing budget. If you're an estate planning attorney, talk to other estate lawyers who've spent similar amounts."
Many lawyers waste time and money on scattershot marketing instead of deploying intentional, scalable strategies. Search engines now use AI to anticipate intent and build firm profiles from review sites, legal directories, guest posts, and media mentions. Local signals and recent user behavior influence search results, so online reputation, content, and reviews must be aligned and consistent to win visibility. Strong marketing begins with clearly defined, specific ideal-client profiles to focus messaging and targeting. Legal marketing vendors vary widely; firms should vet agencies by requesting references from clients in the same practice area and budget to avoid ineffective or costly engagements.
Read at Above the Law
Unable to calculate read time
Collection
[
|
...
]