Scott Hameed, Marketing Technology, Analytics, & Ops at California State University, East Bay
The future of Marketing Ops includes predictive analytics. Scott Hameed speaks to the strengths and weaknesses of predictive analytics today, the future of predictive analytics, and using personalized live chat channels to help persuade customers at different points in the buyer’s journey.
Scott Hameed is currently Marketing Technology, Analytics, & Ops at California State University, East Bay. At the time of recording, Scott was the Manager, Marketing & ABM Technology at Intercom.
Scott has deep expertise in product, process, systems, channels, and analytics. While at LinkedIn, he led an initiative to transform LinkedIn Sales & Marketing through predictive account scoring which led to multiple awards, one approved, and four provisional patents.
At Gibiru, Scott defined new architecture, significantly increasing company valuation. At VMware, he managed the successful launch of a strategic customer database & other systems that were key enablers for the growth of VMware from $3 billion to $6 billion over four years.
What’s the best way to leverage live chat as a channel for messaging?
Let me start with our mission at Intercom: how to make internet business personal. Marketing Ops can relate to that since marketing is personal.
When you go to any website for any type of company, be it e-commerce B2C, B2B, you name it, the idea that you can interact with a messenger which can ultimately then even guide you to a human is a pretty powerful concept. It takes away that impersonal feel to a website. Websites can be impersonal. You can make them personal by including live chat business messaging.
What’s your vision of how predictive analytics is being used today?
When I was at LinkedIn, we built a marketing analytics, dedicated practice based on this whole idea that we should look at analytics as a core function. Predictive analytics played a huge role. We built a custom algorithm for account scoring, which was an industry-leading internal product.
B2C has progressed much faster when it comes to predictive analytics than B2B. B2B of course has challenges, which makes it harder to implement predictive analytics. The key is how do we mine this data to really impact decisions across the entire funnel and beyond purchase.
Content personalization is going to be the next holy grail when it comes to B2C definitely, but also B2B marketing because ultimately you only buy from a company that can persuade you.
You need to persuade them through the right content with the right offers. Building in predictive analytics with content personalization will help with that personalization of persuasion.
What do you see as the future of predictive analytics and data science for Marketing Ops?
First, look at your business problems. Try to understand what type of analytical initiatives that you need to fill those gaps. Remember to think big, please don't think small.
I know you’ll think you don't even have the data for this. That’s okay. Just put your thoughts on that spreadsheet and say here are all the different analytical products or solutions we need to create to really help enable our business.
From there you can go through to see what initiatives don’t require as much effort but can have a bigger impact. Then you can take that vision back to your marketing team and the broader organization saying, you know what? I need resources.
