Key Insights Industry Trends:
1. The Commoditization of Research Execution
- Automating research execution and interpretation opens up more thinking and analysis time (e.g. Research Now standard brand trackers, AYTM analytics).
- Off-the-shelf research solutions (e.g. ZappiStore) provide a right-sized, pre-packaged research project at a great value.
- Do-it-yourself (DIY) research (e.g. AYTM, SurveyMonkey) enables client researchers and consultants to do faster, cheaper research for simple objectives.
Key take-away: Automating non-value added work can be faster, cheaper and more accurate. However, it can never replace an actual human for creativity, influencing and engaging, convincing and telling stories.
2. Bite-sized, Right Sized
- Bite-sized research means surveys that can take 5 minutes (vs. 50) or even a single question at a time (e.g. Google Consumer Surveys, gamified/app research).
- Bite-sized insights can be easily and quickly understood and are a good way to ensure learning is absorbed in an organization (vs. one massive report).
Key take-away: In our information-overload, time-starved world, collecting and communicating data in bite-sized amounts can increase engagement all around.
3. Storytelling Everywhere
- As a research tool—especially in qualitative research, but also larger scale via video in quant (e.g. Voxpopme) or online metaphor elicitation (e.g. Meta4Insight).
- As a reporting tool—think re-telling consumer stories in qual or applying a narrative approach in a quant. summary.
- As an innovation tool—use stories to bring a possible future to life (e.g. Lowe’s Innovation Lab comic books) or collaborate with sci-fi writers to create a future story (e.g. SciFutures).
Key take-away: Emotion is required for action, whether it’s consumer buying behavior or client/stakeholder decision making, and nothing gets to emotions better than a good story.
4. Rise of Machine Learning
- Text analytics and sentiment analysis can derive meaning from big data, social listening, and survey data (e.g. OdinText, Converseon).
- Facial coding can now be done effectively by machines and so opens up new worlds of application and scalability (e.g. Affectiva).
Key take-away: Advances in machine learning mean that computers can take over hours of laborious hand-coding of text and emotion—it’s not perfect yet, but it is much more scalable.
5. Visualization Drives Clarity
- Visual questionnaire design can capture much more accurate data where the subject could be misinterpreted or hard to understand (e.g. VitalFindings).
- Visualizing data and reporting is still a hot topic yet still a major client unmet need. Like stories, visuals make insights easier to understand and more likely to stick.
- Visuals aren’t just for data; they are also essential for bringing strategy to life—think images, video, etc. in addition to text.
Key take-away: Visualization in survey design can help increase accuracy (e.g. visual scales, pictures + words), while in reporting and strategy documents, it’s a way to bring the content to life.
6. Behavioral Research: Actions Speak Louder
- Re-targeting surveys can reach consumers based on a specific online behavior for research—ad effectiveness, site visitors, audience profiling, etc. (e.g. Survata).
- Purchase/ receipt triggered surveys can be a great way to get real time, accurate sample and data on path to purchase, shopper insights, etc. (e.g. InfoScout, Field Agent).
- Implicit research, including affective priming, gathers data indirectly so it can uncover real thoughts and feelings on a range of topics (e.g. Scientient Decision Science, Olson Zaltman).
Key take-away: Identify research respondents via actual behavior (vs. claimed) to increase accuracy. Also, brain science tells us that most decisions are made unconsciously, so don’t rely only on what people say, but also consider implicit and behavioral findings.