Software Ate the World, Now AI Is Eating Software – a Sales perspective
Post-COVID I am working dramatically different as a sales executive. From my experience and discussions with peers, I find that the following tools have been ridden so hard during lockdown by us sales that they are broken beyond repair.
LinkedIn InMail messages
Cold calling
eMailing campaigns
Pure numbers driven Pipeline Generation
Prospects receive too many messages from software sales reps and lead generation tools and are left with no other choice than to completely ignore any message which looks unfamiliar and attention-grabbing. Those overused tools are entirely incapable of reaching anyone anymore.
The following tools are much more demanding, require a high level of energy and collaboration to make them work. Those are my go-to-tools.
Content Creation with the help of ChatGPT
Ecosystems selling with partners
Warm calling with a lot of prior research
Introductions by colleagues to connect with decision makers
Those tools are more genuine and focus on the network and the actual relationship with the decision makers. The tools focus on connecting rather than selling.
Tom Singell, CEO @ Buyersphere argues “Head of Revenue are about to become Head of Ecosystem. We’re moving from direct sales to connect sales”. Further he says that purchasing decisions are changing. There will be hyper-personalized case studies of how any tool fits in with similar organizations. Prospects rather require a relationship person and no more a salesperson to make sure the enablement logistics are met.
Besides that, I would argue that every aspect of customer interaction will be hyper-personalized including but not limited to pricing schemes based on prospect’s business model, partner ecosystem recommendation engines to identify the ideal partner setup constellation per project, and next best actions for legal negotiations of T&Cs.
Tom continues to the see the entire Sales Funnel being replaced by AI, integrations rather than features becomes king, organizations will move from formal hierarchies to dynamic pods and connect to other pods in their ecosystem.
Figure 1: Courtesy of Tom Singell, CEO @ Buyersphere (based on Nested dolls - SaaS edition)
At the same time Veronica Mercado’s article “The AI compute shortage explained by Nvidia, Cursoe & MosaicML” sheds light on the “AI compute costs that are eating up startups’ runway just as fundraising is getting tougher”. Veronica is Principal and Chief of Staff @ SignalFire.
She argues that entrepreneurs might be lured into the idea of cutting costs on training and deploying their models by setting up their own computing infrastructure, essentially constructing and managing a mini-cluster in their garage. However, the more practical approach is to rely on a vendor with expertise in maximizing efficiency.
The inclination to do-it-yourself reveals a shortcoming in the cloud ecosystem, where major cloud providers should ideally deliver such economies of scale that self-configuration becomes obsolete. Regrettably, some prominent cloud service providers package unnecessary managed services for startups, and their egress costs can be intimidating.
Startups are suffering from the “Hotel California cloud model” — you can check in your data anytime you want but you can never leave.
Here you find a sneak peek to our AI Cloud, which enables you to run your AI workloads in the cloud. Thomas Taroni, VP Product @ Phoenix is presenting our set-up of AI Unit, AI Platform, and AI Data Services at our CxO Boardroom event on October 25th in Zurich. There are only a handful of seats left, so reach out to me if you are interest in joining.
Cheers,
Andrew