In his annual letter to shareholders, Jeff Bezos wrote:
Big trends are not that hard to spot (they get talked and written about a lot), but they can be strangely hard for large organizations to embrace. We’re in the middle of an obvious one right now: machine learning and artificial intelligence.
We’re probably not yet in the middle. We’re just getting started in shaping up the next industrial revolution with AI. This post is a deep dive into the why and the how Analytics and Marketing SaaS products will use Artificial Intelligence (AI).
Even if I didn’t plan to correlate the two, this post almost comes as a natural follow-up to what I wrote last week. You can read my last post here: The Modern SaaS stack and the Unexploited Amount of data.
Today’s Marketing and Analytics Landscape
In the mid-2000’s, the digital media ecosystem – born from the traditional publishing industry – began to transform. Back to those days, the world was web-centric. Today’s world not only is not anymore web-centric because people consume more time than ever on their mobile devices, but it’s constantly evolving. The shift we’ve been recently witnessing, from a GUI-driven world towards a CUI world (Conversational User Interface) with new devices like Amazon Echo and Google Home is proof of that.
At this year’s F8 conference, Facebook revealed the intention to double down on his Messanger Platform.
Our goal at Facebook is not to launch a bunch of bots, but make businesses successful on Messenger and give them the ability to communicate with customers.
How do you go about it? That’s where bots come in — it’s not the end, but the means to an end. Bots are there to make sure threads between businesses and people are better. We have the ability to give developers capabilities to build a more successful presence on Messenger so everyone enjoys it.
If you want to have a relevant impact, you need an integrated approach to see what is happening at all customer touch-points and understand how effective you are.
Now, how this has an impact on marketers and analysts?
Most of the today’s marketers are soothsayers. Oracles that don’t know what they’re doing and why they’re doing it. But mostly, they don’t have a precise idea of the impact they have. This is why Silicon Valley distrusts marketing, demeans it, and devalues the people who practice it. Yet, today’s marketers are convinced they’re data-driven.
Analysts from the other side of the coin, are good at managing and manipulating data, but lack at finding patterns, coming up with hypotheses, testing them, and taking (or suggesting) actions on the results.
Data Informed ≠ Data Driven
The more SaaS products you use in your stack, the bigger your data volume will be. All your customers’ data are siloed in all the tools you’re using in your stack.
In this post, I’ve thoughtfully explained the 1-year journey that (almost) every startup does, when it comes down to support marketing and product activities with data.
This is what looks like the final stage after an organization adopted dozens of fragmented tools across their sales, marketing, product, customers support departments.
To perform analysis on your data this is the sad and long carousel you have to take. First (1) extract the data sources siloed in each one of the SaaS product in your stack, second (2) merge those data with your OLAP and OLTP data, third (3) merge those data with your clickstream data. Cluster your data and create some charts on a BI tool (4).
Et voilà, you (think) you’re done!
Bad news, you’re only half-way. Yes, you’ve checked the Data-Informed point, but it takes another 50% for you to have a sense of what the word data-driven really means.
Turning Data into Actions
The rush towards AI Marketing and Analytics Products
All SaaS companies that are able to generate a good amount of data, at a certain point will integrate AI into their products.
Artificial Intelligence impact on marketing and analytics jobs
Every time I read articles on AI destroying and/or replacing jobs I always think to Sir. William Lee.
But when he submitted his invention to the Queen, she declined to issue a patent on the grounds that the technology might cause unemployment among textile workers. He has been refused by Elizabeth’s successor James I for the same reason.
Artificial Intelligence will erode demand for some marketing skills but will increase the demand for others
While a lot of marketing and analytics operations will be automated (e.g. identifying your target keywords, optimizing your ad budget for Adv platform, setting up your ROI metrics in Google Analytics, etc..) others will be created.
The future of Marketing and Analytics is Powered by AI
According to Barton, the future is a diverse and modern marketing team, made up of the clever analytical marketer who uses big data to make smarter decisions, and technology will facilitate this change.
And I couldn’t agree more.