LinkedIn wants to make more money from advertising and it’s got a cunning plan to get advertisers opening their wallets. By handing over more data on its users, the network is confident ad spend will rise significantly and it’s teaming up with DataShift to make it all happen.
For LinkedIn advertisers this means a bundle of new info on the kind of ads users click and the topics they’re talking about most. So better targeted, more relevant ads will be coming to the network soon – and that’s good news for everyone involved.
LinkedIn introduces PYLON
LinkedIn is introducing PYLON for LinkedIn Engagement Insights, a “customizable reporting API solution that empowers marketers to make data-driven content, creative, and targeting decisions on LinkedIn’s professional network.”
DataShift is providing the platform itself and LinkedIn is simply providing the data (note: LinkedIn isn’t making any money from providing this data, it simply wants to encourage more advertisers).
In all the official statements from LinkedIn, the network is keen to reassure its users that privacy will not be compromised through PYLON but it’ll be interesting to see what privacy changes emerge over the coming years.
Data-driven advertising on LinkedIn
PYLON marks LinkedIn’s biggest move into data-driven advertising to date. Until now, targeting users on the network has been quite simple but getting data feedback on their interactions remains elusive.
This is going to change with PYTHON, which will provide vital insights on ad clicks and topics on LinkedIn. It will also empower advertisers to optimise their campaigns based on user data and improve results over time. Here’s one use case Russell Glass, VP of products and marketing solutions at LinkedIn offers up:
“For example, let’s say you’re a marketer at a software company interested in reaching IT decision makers in the US, but you aren’t sure how to target them or with what content. Using LinkedIn Engagement Insights, you can discover that this audience is most engaged with SaaS, business intelligence and “big data” themed content. This information can help you recognize how to best reach them on LinkedIn, and with what content, in a way that works within the context of your marketing strategy.”
Only time will tell if PYTHON increases LinkedIn’s advertising income as much as it hopes but, in the meantime, it means a stronger marketing channel for everyone using it. Hopefully, it works out to be a win-win and the network continues to adapt as a data-driven advertising platform.