AI implications on Marketing and Analytics

(leonardo) #1


Last week I’ve been reading dozens of articles on AI and the impact on SaaS. Unluckily I didn’t find something good enough, so I decided to write my own post where I gave my own thoughts on the impact that AI will have on Marketing and Analytics SaaS products.

Although Artificial Intelligence has become a buzzword (widely used in sales pitches, ad copy and new app landing page), it’s one the big trend we’re living.

So I ask you the very same question I’ve asked myself a few days ago, how AI will shape the next generation of marketers/analysts and the next generation of Marketing and Analytics SaaS products?

(Kevin W) #2

Really great article – thanks for writing / sharing Leonardo! I especially like the distinction of how we’re transitioning from “Want” to “Need” right now.

I think one point that’s been missed in the current AI buzz is the fact that currently AI applications are large in impact although narrow in scope; the former means that AI is really important, but the latter means that it isn’t (yet!) a panacea for all of one’s business challenges. We’re at the point where one can very effectively optimize existing marketing + analytics processes, but we still require human beings to setup, train, or otherwise steward the algorithms since they tend to have very limited goals. The current buzz makes it sound as if you can press a button and have AI run your entire business but the truth is more nuanced. At least for now, your self-driving car won’t beat you at Chess :slight_smile:

Here’s another article on AI that I liked, although I’d say that I’m a bit more optimistic about near-term AI than the tone that it strikes:

(leonardo) #3

Yep, good point Kevin.

Here’s the difference from General and Narrow AI.

ps. another very nice article about AI to add on my list, ty

Would love to know what @andrewchen think?

(Declan Dunn) #4

Also enjoyed this article, AI right now is in its infancy and growing fast. From my own limited bias as a growth marketer, machine learning is having some early impact. Yet so much of the human element is involved.

Interesting questions about AI - will the humans behind it allow it to think openly and freely, or will they build in constraints, rules, and essentially biases so the AI serves their needs? Naturally this will happen, but the idea that we’ll just let the machines do what they want is a utopian world I’d like to live in…still the world we live in is run by humans with agendas.

Such interesting times coming up in the next 10 years, when AI is seriously embedded in our lives and our businesses.

In the spirit of sharing articles, an old business friend who ran LinkShare has popped back up in the AI conversation, targeting SalesForce and other CRMs that are entirely inefficient in managing marketing and sales with his company, Collectivei.

(I’ve got no association with this, other than deep respect for the management team who are seriously good at executing)…

“While conventional sales organizations used CRM to count sales activities and manage sales workflows, the three founders theorized a better way to predict the outcome of the sales process was to study the buyers. They surmised that by building a network of sales organizations and then applying emerging data science technologies, they would be able to identify patterns of how enterprises around the world actually made their buying decisions.”

Many of the ways we work today are broken, interesting to see how many we can fix. Growth for me, in business, depends on a much closer integration of sales and marketing, not the silos of isolation we see in many corporate structures today.

Collectivei’s challenges to CRMs - that essentially they force salespeople to game/not be transparent, is something I’ve experienced. And Salesforce is so cumbersome in my experience, forcing humans to create rules. This is one case where getting humans out of the way, to me, really makes sense.

(leonardo) #5

Thoughtful @declandunn – but I agree. As I tried to explain in the post, we are living an era where we (finally) have the data, but we’re not so good at interpret those data and take meaningful decisions. This is not just valid for decisions strictly related to product (what users want/use) and marketing (what works and what doesn’t), but also for management.

In my previous companies I saw many sales (inside sales) ppl fired after 2/3 weeks, not because there were underperforming but because the gut feeling of their managers told so.

This is why I’m so bullish on AI applied on everything and I found extremely valuable companies like