Do you know why your CMO needs artificial intelligence NOW?
Because:
CMOs must show measurable financial results for the budget they invested!
Wonder how AI relates to financial results?
I’m not surprised since the answer may not be obvious.
With an ever-increasing number of smart devices, apps and methods, consumers have more and more ways to get information and create content digitally.
In the process, they create an explosion of data for marketers to track and analyze.
This new information may be difficult to associate with your organization’s existing data since internal data may come from legacy systems, be siloed in different departments, and/or be incomplete.
As a result, the data from various sources must be collected, cleaned and organized before you can use it. This work requires data experts who understand how to accomplish this.
Once you have quality data, AI can quickly and cheaply analyze it and provide insights that yield better and more measurable marketing results than humans by:
- Analyzing bigger datasets in very short periods of time,
- Detecting trends humans may miss, and
- Creating personalized audience experiences at scale.
But don’t worry—we’ve got your back—even if you’re not a CMO!
We’ll show you how to generate measurable financial results your C-suite will understand using AI by:
- Examining your current marketing analysis and data,
- Showing you how AI can help solve your marketing challenges, and
- Explaining how to start to use AI in your organization.
CMOs Biggest Problem Is The Inability To Prove Financial Results
63.8% of CMOs across different sectors say their top business challenge is showing the financial impact of their marketing activities on a regular basis according to The CMO Survey (Deloitte, Duke University-Fuqua and the AMA 2019).
SO what can CMOs do to get financial results for their marketing initiatives?
Use marketing analytics and data to measure actual financial results against business goals and marketing KPIs.
While this advice sounds good, the reality is that marketers lack the necessary analytics and data.
Specifically according to the CMO survey:
- Use of marketing analytics reached its highest level in 6 years and is expected to increase,
- BUT only 43.5% of companies across sectors use marketing analytics.
Translation:
Seat-of-your-pants decision-making guides 50+% of marketing choices!
While businesses continue to make small gains to track financial performance:
- Only 36% of CMOs use quantitative data to make marketing decisions,
- 50.7% of CMOs have qualitative data to support marketing decisions and
- 12.9% of CMOs lack both quantitative and qualitative data for marketing choices.
Further, while not explicitly mentioned in the CMO Survey, different skills are also needed to support and analyze this increase in data-related work.
As proof, the Top 10 Most In-Demand Hard Skills for 2019 according to LinkedIn are:
- Cloud Computing
- Artificial Intelligence
- Analytical Reasoning
- People Management
- UX Design
- Mobile Application Development
- Video Production
- Sales Leadership
- Translation
- Audio Production
Like marketing analytics, finding and hiring top marketing talent with these skills requires both budget and time. As a result, having knowledgeable staff can be a competitive (albeit expensive) advantage.
Why CMOs Are Drowning In Data And What Can They Do About It?
The challenges exploding amounts of data create for CMOs and marketers fall into 3 general topics:
- Explosion of data related customers’ digital activities and user-generated content.
- Need for quality data to drive useful, measurable marketing outcomes.
- Issues of data control, security and privacy.
CMOs Face Explosion Of Customer Created Data From Digital Footprints And Content
Marketers must track more and more data from digital footprints left by expanded smart digital device use and data-rich user-generated content including comments, photos and videos.
Further, marketers must not only track this growing amount of information from customer actions, but also, find emerging trends and meaning.
To appreciate the sheer size and complexity of this ever-increasing amount of information, IDC Research developed and organized The Global Datasphere in November 2018. It consists of 70 categories of content creation/capture devices and includes embedded systems in devices. It falls into 4 broad categories based on device non-entertainment imaging, entertainment, productivity and voice.
So you need artificial intelligence to analyze it, determine trends, and predict future actions.
BUT CMOs Need Clean, Useable Data To Get Measurable Marketing Outcomes
Before you can mine this mountain of data for business gold, it must be cleaned and made useable. Otherwise, you get garbage in; garbage out.
In 2012, IDC found:
- 23% of existing data would be useful if tagged and analyzed.
- Only 3% of useful data had been cleaned and tagged, and
- Less than 1% of data had been analyzed.
To make your marketing data AI ready, follow the 6 Cs of Quality Data Framework developed by Katie Robbert of Trust Insights.
- Clean. Has been prepared and free of errors,
- Complete. Contain no missing information,
- Comprehensive. Answer the question(s) being asked,
- Chosen. Contain no irrelevant or confusing data,
- Credible. Has been collected in a valid way, and
- Calculable. Must be workable and useable by business personnel.
CMOs Face Data Challenges Beyond Quality
In addition to cleaning and preparing your data for AI use, your business must protect the security and privacy of the data.
Translation:
- Get permission to use the data when it contains personal and confidential information.
- Protect the data your business has based on the type of information and related security needs and/or laws.
As the recent legal cases and fines involving data supplier Equifax and social media platform Facebook underscore.
To illustrate the increased business challenge:
In 2012, consumers created 68% of the digital information BUT businesses were responsible for protecting 80% of it. (IDC Research 2012)
Further, you need access to other related and relevant data to get a holistic view of your audience, prospects and customers. But this information may be held by third parties who are unwilling or unable to share or sell access to it.
As Sir Martin Sorrell, former head of WPP points out:
“Walled gardens are dominating digital business at present. Their reluctance to share data is increasing,”
In his view, the fearsome 5 global companies are Google, Facebook, Amazon, Alibaba and Tencent
What Can CMOs Do With This Data To Get Measurable Results? Use AI
To get measurable results from this data that your C-suite understands, your CMO needs artificial intelligence.
- First check that your marketing problem requires marketing artificial intelligence with the 5 Question AI Test.
- If your problem can use marketing AI, then apply one of the 5 Types of Data Solutions to yield measurable results.
Start With The 5 Question AI Test
MIT Tech Review’s Karen Hao outlined her 5 Question AI Test to determine whether a system truly uses artificial intelligence.
- Can it see? AI technology can identify what it sees using computer vision and image processing.
- Can it hear? AI processes, transcribes and offers a useful answer.
- Can it read? AI reads the information you type, analyzes the text for patterns, and provides a useful response.
- Can it move? AI moves without help based on what it hears and sees. It doesn’t need a programmed path.
- Can it reason? AI looks for patterns in massive amounts of data and then uses these patterns to make decisions and continually get smarter.
In addition, Hao created a flowchart of her 5 Question AI Test.
Want to increase your Artificial Intelligence?
Then get Karen Hao’s weekly newsletter, The Algorithm from MIT Tech Review. (It’s FREE!)
5 Reasons Your CMO Needs Artificial Intelligence To Drive Measurable Results
To get better, more measurable results from their marketing faster and cheaper, CMOs need artificial intelligence to solve for 5 types of data challenges. Together these comprise the 5 Us of Data Framework developed by Trust Insights’s Chris Penn.
Each type of data provides a reason for your CMO to use artificial intelligence to solve an existing marketing challenge and to improve their business results.
Further, by using AI to significantly improve and speed up your marketing analysis, you get results that focus marketing activities to yield measurable results. Even better, they’re in terms that your C-suite understands!
Reason 1: Mine Unstructured Data To Find Major Trends
By itself, unstructured data provides no useful marketing insights. So use AI and data mining to find insights into big trends.
For example:
AI shows the difference between the attributes businesses want in job candidates versus what candidates seek in new positions. This uncovers a serious problem: businesses and candidates don’t use the same language!
Reason 2: Analyze Unknown Data To Find Top Influencers
To discover the top influencers (or other target group such as brand names) analyze your unknown data to extract influencers for reputation management.
For example:
Analyze the tweets related to a specific topic or event to find the top influencers. While there are spreadsheets showing the aggregated data, here’s an easy-to-understand visual presentation of the top influencers from a recent conference. (Hat tip: Chris S. Penn)
Reason 3: Analyze Unclear Data To Determine Competitive Analysis
Even if you can analyze the marketing data you have access to, the results may still not yield actionable recommendations. Penn refers to this as unclear data.
For example:
Get strategic insights for search marketing using AI to assess your business’s content performance based on search results. By allowing the machine to continue to learn, it’s able to show:
- How your business currently ranks for its set of search terms,
- Which key search terms to protect from competitors and others, and
- Which search terms to proactively focus new content on.
Reason 4: Identify KPIs and Insights From Unfocused Data
Use AI to analyze unfocused data to identify KPIs and insights. Then use these results to determine where to focus your marketing efforts to improve results. This will help you to do better than 2/3 of your peers as highlighted in the CMO Survey above. Use it to associate content with the purchase process and more.
For example:
Apply AI to your website analytics to find the your Most Value Pages Report (aka: MVP Report). Then further optimize these pages for conversations and next steps.
Reason 5: Unprepared Data
Through the use of AI, the machine continues to learn from your data. As a result, it’s able to perform predictive analysis. This provides recommendations to improve your content marketing.
For example:
By analyzing your search keywords, AI recommends the content you need to create. This provides an editorial calendar based on search needs.
If My CMO Uses Artificial Intelligence What Happens To My Job?
While using artificial intelligence to support marketing decisions yields improved analysis and more measurable results, what about the existing mindset among employees and the C-suite?
Fear not my fellow humans!
Because:
“AI will take away the tasks, not the jobs!” according to the Brookings Institute.
Further, artificial intelligence can’t replace your ability to:
- Show empathy,
- Make judgments,
- Have life experiences, and
- Build relationships.
How Experienced AI Marketers Respond To Corporate Naysayers
According to Unbounce’s Carl Schmidt:
“It’s not the technology that will hold you back. More than likely it’ll be the culture of the organizations you’re working with.”
Translation:
Your biggest hurdle to using AI to improve your marketing is the hesitancy, skepticism and excuses from member of your team and others in your organization.
Instead of worrying, listen to PathFactory’s Elle Woulfe:
“Make marketing decisions by combining the power of AI with human judgment,”
This diagram by Eric Colson illustrates how AI machines and humans work together.
How To Add AI To Your Marketing Organization: What Other Marketers Say
To use AI in your business, PR2020’s Jessica Miller asks:
- Where do we spend our time?
- What repetitive tasks can we automate?
- What data do we have access to?
By contrast, Grant Thorton’s Sara Hocking says to start with a specific business problem and set a schedule for your marketing AI experiment. In her words:
“If you don’t clearly define the problem, people won’t use it.”
To test how to use AI, Grant Thornton created a cross-organizational team to with volunteers. Working together, they tested how AI could help reach specific business goals and solve problems.
Further, Hocking recommends:
Take the time to understand the AI use-cases. But stay focused on the business problem you’re trying to solve.
Why?
Sometimes the answer to your problem doesn’t require AI. Instead, you may need to change processes or another technology.
Like Miller, Hocking asks:
- Who owns the data?
- Where is it?
- How do we get access to it?
Lastly, Hocking suggested:
Ask your vendors to educate you on how you should use AI in your organization.
Data analysis is a team sport that includes stakeholders, engineers, scientists and analysts according to Pandata’s Cal Al-Dhubaib.
To become a data-driven organization:
- Get buy-in and alignment across your organization. Empathize with stakeholders and address cross-department boundaries. Start small with a focus on ROI.
- Build trust across your business. Tap internal champions to gain trust. Then communicate project assumptions and definitions. Lastly document your data sources.
- Show value with performance reporting. Continually test and document performance. Also make trusted data accessible across your business. Lastly, document each data solution version and associated ownership.
Need more proof why your CMO needs artificial intelligence? Check how the Cleveland Museum of Art used AI.
Why Your CMO Needs Artificial Intelligence Now Conclusion
Attention CMOs:
Artificial intelligence doesn’t replace humans!
Rather:
Artificial intelligence helps unlock your organization’s human potential. In the process, it improves your marketing performance and yields measurable business value!
As a result, you’ll be able to communicate your marketing strategy’s contribution in terms your C-suite understands.
Result:
You’ll be a business champion!
But don’t rush to add AI to your MarTech stack!
Why?
Because you must first define your top marketing challenges to determine where AI can make a measurable difference. Often, it’s by eliminating repetitive work or analyzing massive amounts of data faster.
Then you must find where the relevant data exists across you organization, related platforms and agencies. Further, you must ensure that the data is clean and protected.
Remember:
Your objective is to save your employees time to allow them to focus on the human element of their work.
Like Grant Thorton’s Sara Hocking:
Start by taking baby steps to ensure that marketing artificial intelligence adds value to your marketing mix.
And that it can be integrated into your existing MarTech stack and processes.
Happy Marketing,
Heidi Cohen
PS: This article was inspired by MAICON19 and its great speakers. (Hat tip: Paul Roetzer and Sandie Young of the Marketing AI Institute.)
CMWorld 2019 features over 150 sessions covering two dozen tracks.I’ll be there along with 200 other speakers from around the world.Register today. Use my code: COHEN19 to save $100.
Photos by Heidi Cohen unless otherwise noted.