How to Clean Up Your LinkedIn Connections

How to Clean Up Your LinkedIn Connections I’ve been in recruitment a while, even back in the day before PCs and when CVs littered the halls like something from the movie Brazil. Recruiters hoarded paper like there was a war on, collaboration happened only at work nights out (do you get my drift?) and the CRM (which was only used by the massive team of CV administrators) was the old, flea-ridden dog in the corner. As the digital wave has swept over us, we have collected more and sourced harder. Our LinkedIn connections number on our profile is a badge of honour â€" new consultants stride towards the 500+ at speed! This is not sustainable or necessary. Why you should clean up your act (and connections): The algorithm in LinkedIn (people you may know, jobs your may be interested in, groups you may want to join etc…) â€" these “personal shoppers” rely on a clean and tidy contacts database to add value and give recruiters data which makes their day better. Recruiters and USPs?  I rarely see genuine USPs â€" but I do work with recruiters who have superb databases.   Data which is better than their clients’, candidates’ and competitors’ â€" this could be a great USP … “we know people”, “we can get to them quickly”… Speed â€" never before has speed been so high a priority for my clients.   It’s fair to say that many clients of the average agency recruiter want candidates, but they’ll settle for anyone who can do the job, and not necessarily wait for the best candidate.   This is reflected in typical case studies around recruiters competitors with numerous agencies for first past the post talent. There are 2 camps when it comes to the how to build your network: Connect with anything “in a skirt” and hope that when it gets to 3am and everyone’s gone home, there’s still a “unit” to score. (I worked in recruitment in the early 2000s and picked up some interesting language!) Be strategic â€" connect with people up and down the food chain in your industry (and the industry of your ideal talent and clients). (Guess which one I subscribe to!) So, if you agree that a clean and tidy database is one which is an asset, helps you do your job better and persuades your clients to get back to their desk and let the experts take care of the recruitment piece, then check out these 3 (free) ways of keeping your data clean. InMaps â€" check out this video, then run it for yourselves.   Don’t worry if it takes a little while (it can do) but it’s worth it.   You’ll see your network, you may even see randoms* that you rarely should “cull”.   I often run sessions and demo this and everyone coos like doves whilst seeing who they are really connected to.   Plus a great Ops Manager I know tells me he uses this to test the real value of a prospective employee’s network â€" Oh I love that! (Thanks for the tip Dave!)  Your LinkedIn Contact screen â€" study the “congrats” pane at the top.   Are there any randoms* in there?   You’ll see people’s birthdays, work anniversaries (look out for those lovely “I’ve been in my role 3 years â€" help me get out of here” contacts.   Look for “I’ve changed my role and forgotten to call you” contacts â€" bin or re-ignite. Bullhorn Reach â€" now step away from the “look how easy my job is â€" I press this job advert button and loads of money” button â€" and “reach” for the radar instead.   Surely you’d love to know when people appear to be getting itchy feet (Potential Movers”), or when they’ve been promoted / moved businesses (Recently Changed Jobs). Spend 5 mins a day on this and you’ll do a fabulous job of creating a database which pays you back every time you search it (and every time LinkedIn offers you people, groups and jobs).  Let’s also not forget that whilst you are doing this weeding, you may find hidden gems that you can re-engage with. It’s never been easier to collect people, and indeed remove people from your LinkedIn contacts â€" make sure you spend time developing the database you need, rather than simply scalp hunting. *Randoms defined: people you connected to when you’d probably had too much to drink at the club #BeerGoggles