View from Silicon Valley

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Talk to different insight teams in Silicon Valley and you’ll find that researchers are increasingly faced with a million ‘whats’ and very few ‘whys’. It’s great to have data describing what’s happening within your product but – without context or explanation – then you’re dealing with Blind Data and not Big Data; it’s the ‘whys’ that are golden.

Sifting through the ‘whats’ to find the ‘why’ is a problem that’s sharply felt in Silicon Valley, but it’s also a problem that will continue to be felt by more insight teams as brands invest in expanding the data they collect and use every day to help make decisions. 

Clearly this is not a new trend but it’s one that continues to pressure the relationship between agencies, research teams and stakeholders who are increasingly self-sufficient when it comes to information. Here, I’ve seen in-house researchers and agencies alike respond rapidly, and become focused on being their stakeholders’ connections to context, offering an external perspective on their business and only tackling the ‘why’ questions.

This is a big change from the past role of researchers as measurers-in-chief, analysing product adoption, customer trends and supplying numbers and dashboards to their CMOs. In Silicon Valley – and increasingly beyond – that’s becoming the domain of behavioural data and data science teams. Instead, researchers here are embracing their roles as heads of why.

As a result of this shift, the function of agencies here has had to change in a way that – I think – reflects the future of client-agency relationships in industries awash with data. The most productive relationships I’ve seen in the US between data-rich companies and their agencies revolve around three pillars:

1. Question-storming

The physicist Richard Feynman once said: “I’d rather have questions that can’t be answered than answers that can’t be questioned”. We think about that a lot in our team. Finding the perfect question to ask of our data is critical to finding the ‘why’. Rather than brainstorm answers, we instead have to know what questions we need – a process my VP calls question- storming. Agencies that spend time helping us find those questions are the ones we ask to assist us to answer them.

2. Extend clients’ analytical capabilities

Despite the amount of data in tech companies, thankfully not every researcher is going to be a statistician. Indeed, it’s the diversity of our backgrounds that make research teams so interesting to be a part of. However, it’s increasingly important that clientside researchers can talk to – and defend their work – to an audience of engineers and data scientists who are themselves postgraduate mathematicians.

Agencies that can offer specialised analytical support to their clients by keeping up to date with the latest trends in data analysis are highly valued and are always going to be preferred to those wedded to older techniques.

3. Diversify methodologies to complement what clients already have

I think I’ve done more qualitative research since moving to San Francisco nine months ago than in the previous four years of my
career. I’ve seen traditionally quant-heavy agencies over here all but abandon survey-based research when dealing with tech companies and concentrate instead on highly-focused, deep qualitative research instead.

Qualitative research is often revered here as it is uniquely powerful at finding the ‘whys’. Agencies that fully understand what is already being measured internally can then diversify and focus on being the qualitative yin to their client’s quantitative yang.

So there we have it. The three pillars of client-research agency relationships in Silicon Valley, and a possible model for the future – question storm, extend, diversify. QED. 

Matt Taylor is consumer insight lead at Twitter