The rise of programmatic buying has impacted not just delivery and pricing, but the sales process itself. Publishers are scrambling to adjust their sales teams and processes. A year ago, many large publishers were adamantly refusing to sell their inventory through exchanges. Now, most of them have jumped on the bandwagon, albeit kicking and screaming. The latest to fall was Turner, which this week announced it was starting its own in-house exchange.
The ad sales model is being disrupted and it’s impacting the role of the digital salesperson. The traditional sales force, selling premium advertising using the direct sales, relationship model, is being edged out of the picture. Media sales people, who spent their time coaxing media planners and entertaining clients, find that trying to build custom ad solutions is becoming a tough sell. Now, part of their job has been replaced by a machine–one that is more efficient, more data driven, and less complicated.
Technology has changed the way ads are traded. Programmatic is delivering eyeballs and audience with better speed, more accurate targeting and more efficiency. The automated technologies can reach many more buyers of inventory than a legacy direct sales team could. It’s a numbers game.
The new profile of the ideal sales candidate has drastically changed. Now companies need someone much more data driven; more of a data wonk than a relationship person. What worked five years ago doesn’t work today. Larry Herman, of EyeReturn Marketing, deals with this every day:
“From our perspective, this is very different from the traditional online media sale. While personality and the ability to navigate both the agency and direct marketer ecosystems are key, we need folks that understand technology, aren’t afraid of math and can convey how we’re able to sell an audience.”
EyeReturn, which combines a DSP, ad server and verification and reporting systems, would need more than just a classic media solutions salesperson to move the needle. It’s hard to have a relationship driven sales person talk to a media trading desk.
Publishers are finding it harder to sell that premium space, though some have not given up. Turner is trying to hedge its bets a bit, as it steps gingerly into the programmatic world. Its exchange is accessible only to its ‘valued partners’ and will require a personal relationship with one of their sales team. Premium is becoming a smaller part of the publishers’ revenue. Programmatic is not just for remnant inventory anymore and it’s freeing up those human resources.
Transactional buying and legacy sales teams are usually two separate approaches. Some publishers have tried to keep both channels going, but it’s not a natural pairing. Many publishers are siloed, with direct and indirect sales channels not mixing. And don’t even try to add analytics to their mix. The structure of many sales teams is old school, and can hold things back.
One way some publishers handle this oil and water mix is by paying sales people for programmatic buys. No matter how the deal gets done, the sales team is compensated. This keeps the sales team motivated, saves the publisher from having to redo their compensation structure, and keeps all the sales components on the same team.
in summary, it will take some evolution on the part of those classic media sellers to compete in today’s Big Data market. Yet I believe, as with many trends, they are cyclical. Relationships have always driven sales, and eventually the machines will combine with the relationship, and that will be a happy day for the ad sales executive.
Title image courtesy of Shutterstock.
Time is running out to feature your company in our inaugural Mobile Vendor Reader Survey.
Marketers create personas to better understand their target audience and what it looks like. If marketers can understand potential buyer behaviors, and where they spend their time online, then content can be targeted more effectively.
What’s behind a successful data-driven marketing strategy?
Audience targeting can be challenging in social media, especially when brands make quick assumptions about their target users. How can you avoid generalisation and what are the real benefits of it?