Posted By Lisa Horwich,
Tuesday, April 30, 2019
Updated: Tuesday, April 30, 2019
Why Quallies Should Care about Marketing Technology (MarTech)
The “Rise of the Machines” and how We Got Here.
When I graduated from business school back in the late ‘90s I never dreamed I would become a total tech geek…in fact, I really thought I was going to be a high-powered consultant (think McKinsey, Bain, BCG). Instead, somehow, I found myself implementing large-scale computer systems (fears of Y2K!) and then became a product manager for a small software company. My journey to tech geekdom had begun without me knowing it.
Fast forward to today. After spending much of my time working on quantitative and qualitative research for large tech companies, I can honestly say that I really love learning and studying technology.
With this in mind, about 2 years ago, a prediction from Gartner (the big technology industry research firm) caught my eye – their analyst Laura McLellan predicted that by 2017 CMOs will spend more on technology than CIOs. She was almost correct – it happened in 2016, a year ahead of schedule.
Think about it. Marketing departments are now spending more on information technology than the department that is responsible for a company’s technology infrastructure. Crazy, I know!
This has led to a proliferation of companies clamoring for a piece of this MarTech pie. From 2011 when 150 companies offered MarTech solutions, we are now in 2019 looking at over 7,000 companies competing in this space.
What is the aim of all these solutions? More importantly, what has changed with CMOs to prompt this massive investment in technology? It boils down to three main factors:
Most CMOs now share P&L responsibility. Instead of just being a “cost center,” marketing is looked on as fundamental part of revenue generation.
Marketing funds and designs the entire cross-functional customer experience (CX). If you think of CX holistically from generating awareness through post-sales feedback, it makes sense that marketing is in charge.
Finally – and arguably most importantly – with the soaring costs involved in attracting, maintaining, and growing the customer base, marketing now has to justify the ROI of their activities.
CMOs are turning to data-driven solutions that help them deeply understand every phase of the customer journey – tracking and quantifying the ROI of all marketing activities along this journey. They are also investing heavily into solutions that personalize the customer’s experience with the hope of converting these interactions into greater sales opportunities.
Technology Solutions and Their Uses
As researchers, we need to know the types of technologies where our clients are spending significant portions of their overall budgets (~30%) so we can recognize where we fit as human insight professionals. We don’t have to be experts in tech, just conversant — so when we walk in the door and our clients say they are using a new “Artificial Intelligence email optimization tool,” we understand what that is and can talk about how our services complement and augment this tool.
I’ve put together a few charts and tables outlining some of the fundamental building blocks of these solutions. Most MarTech offerings are powered by technologies such as Artificial Intelligence, Machine Learning, Business Intelligence, and Real-Time Analytics. I find it useful to see the interaction of these technologies with a chart:
To understand definitions of these technologies and common uses, this table is a quick reference (CAUTION: Tech speak ahead):
Unified customer data platforms, predictive analytics, and contextual customer journey interactions.
Any system that learns from past data to make judgments about previously unseen new data.
Optimize ad campaigns and other metrics, predict churn.
Opportunities for Quallies
Many of the technologies outlined above have inherent limitations – which I like to think of as “opportunities” for qualitative researchers. Most of the limitations center around the data – quality (how good is your data) and quantity (do you have enough of the right type of data). In addition, the other major limitation is having enough marketing content – a major bottleneck in the quest for personalized customer engagement.
Decisions are made solely on data – past and present.
Use the data as a launching point for deeper qualitative analysis.
Existing data is not predictive enough for decision-making.
Create and maintain communities focused on pinpointing predictive behavior.
Need exponentially more messaging content for personalization.
Assist in narrowing target messaging by identifying key characteristics valued by customers.
Insufficient data to train the machine/AI.
Provide personas and other descriptive metrics to help “train” algorithms.
Lack of “industry specific” attributes.
Create detailed feature lists to describe the unique features inherent to that industry.
While the ideas above are great tactical opportunities, strategically, our most important job as qualitative researchers to remind our clients how, in a world of automation, humanizing the experience of individual customers is key to authenticity.
Lisa Horwich is the founder of Pallas Research Associates, a B2B-focused research and consulting firm located in Seattle, WA. She is a self-ascribed tech geek and loves talking to developers, IT decision-makers, and CIOs. She also co-chairs the QRCA B2B SIG.