My notes. Any errors are my own. Make sure to read Ian’s at the bottom, nicely insightful.
Why Digital Data is the Fuel you Need to Make Fire Content, By James Lachno and Nicholas Boles, Edelman
74% of people avoid advertising.
Relatability is twice as important as popularity.
Audiences are now in control [i use multiple ad blockers, VPNs, and privacy browsers]
We need to always be relevant and valuable. We need channel agnostic stories. We need to be creative at the core.
The Story Planning Cycle
Identify your three or four key audiences. “Beats” as you might call them in journalism. Create a brief for each audience. What do people search for when they’re part of one of these audiences. What are the search and news trends on a seasonal level for these audiences. Conduct a collaborative content plan to be focused on the needs that are relevant to each audience. Build content, and decide on who, what, when, where to publish. Measure when people actually search for the various types of content to identify earned, organic engagement.
Going Viral Using Real Time Data
Need to recognize when a real time event could become a viral sensation that is in line with the business. E.g., #DartGuy smoking cessation.
- Bake data mining in your strategic processes.
- Collaboration is King
- Bring clients on the journey with you
- Speed is better than perfection [oh, remember the last speaker said that too!]
- Don’t self censor
Unlocking ROI Through Advancements in Analytics, By Hilary Borndahl, Kantar, and Nick Necsulescu, World Vision Canada
Started the presentation by having audience log into menti.com: 42 57 80, a live voting website used throughout the presentation. [where I voted for “cat” about 300 times. Really nice live charts and word clouds based on our inputs. But it does draw attention away from the presentation.]
Marketers want balanced measurement but skew towards short-term tactics. Many feel they are leaving opportunity on the table.
Channel strategy and media tactics need to be tailored to address business objectives.
Drivers of ROI on TV media: Creative is huge, followed by market buy.
Niche brands are taking over the jobs that used to be done by key players.
2.3 million conversations evaluated. Ordered the data by brands, products, lifestyle, benefits, product features, and more
Brand by location was of key importance. Correspondence analysis identified opportunity gaps in the context of trends. They built a creative content strategy around these moments in time – celebration and togetherness.
Machine learning and AI need to be integrated earlier into the process. Look at data second by second to predict branding, impact, facial coding emotion.
World Vision tested 14 creatives using AI/machine learning. AI traces KPI scores over a video duration to see impact of each creative. The model shows which ads have impact, generate spikes, where the spikes occur. Included a few ads that have been previously evaluated in a traditional form. Results correlated highly with models. Awareness was the only metric that did not correlate.
Love Can Do Anything was the winning ad.
Stuck in the Middle with You, by Ian Ash, Dig Insights Inc.
“Feel free to disagree with me or be offended.” 🙂
The world used to look like this: Automated/DIY, mainstream MR, high end custom, analytics/big data, strategy consultants.
Now the middle is squeezed: automated DIY and strategy consultants are squashing out the rest.
Strategy companies are on a buying spree. Automated companies are getting all the funding – Zappi, voxpop, qualtrics, surveymonkey
Private equity is throwing money at scalable companies.
SMall companies are competitive with companies that don’t have to generate profit – they just have to have a path to profit. So the small/medium companies suffer.
More consolidation is on the way.
Expect mainstream MR to buy automated/DIY companies.
Automated DIY will compete more directly with mainstream MR.
End clients are starting to buy analytics firms – McDonalds, Visa, Unilever have all bought analytics firms.
AI is the seasoning salt of software. Everyone says they have it, most actually do not.
AI is for prediction models, determining sample sizes, codon open end responses, statistical analyses, finding insights.
Merged data creates holistic approaches. Including sales and volition perditions, segment prediction models, price elasticity models, product optimization.
Blockchain allows buyers to interact directly with individuals. Protests privacy, incentives accuracy, creates fair compensation, provides data usage and payment transparency.
How to compete.
We all need to have automated methods. Develop data science capabilities. Increase customer service. Partner with digital ad agencies. Used merged data approaches with API integrations.