According to predictions, by the year 2020 artificial intelligence will manage 85% of customer interactions. Yes, AI has that much potential. And one of the principal ways business owners are looking to tap into this potential is through CRM applications. It’s ironic to think that non-human, artificial intelligence can help humans bridge the communication gap, but that’s where we are in this brave new world.
We’re already seeing evidence of the raw power this technology possesses. Forget mere customer service chatbots—advances in machine-learning mean AI can take over formerly white-collar business processes, everything from research and administrative tasks to the accumulation and organization of data.
That means we now exist in an advertising landscape where smart data discovery is providing insight into business data and statistics more than ever before. This in turn sharpens the blade of prescriptive analytics and provides us with more tools to glean market insights. With AI on the rise, many professionals in the insight sector are becoming rightfully nervous, wondering if there will even be a role for humans in this new AI-driven reality.
The good news is that not only will there be a role for human market researchers, AI can actually help them supercharge the insight and marketing process. Here are a few categories where we’re already seeing progress on this front.
Most market researchers know that there are few better ways to foster long-term brand-consumer relationships than through personalization. Today’s consumers want brands that know who they are and speak to them directly. Let’s take a look at email marketing as an example. This is a cornerstone of any solid digital marketing strategy, and the proof is in the pudding. Among other statistics:
Personalized email messages improve click-through rates at an average of 14% while boosting conversions by 10%.
Emails with personalized subject lines are 26% more likely to be opened.
Personalized emails deliver six times the transaction rates.
This is aside from that famous statistic showing that for every dollar an advertiser spends on email marketing, they see a $38 return in revenue.
Consumer segmentation in email marketing is still vital. But now market researchers can extract customer data with the help of AI. These new AI-fueled platforms can identify trends and predict responses according to individual interests based on multiple variants. This is the supercharge of insight that those in the market research sector should welcome.
This efficiency will support researchers and in turn allow marketers to do their job more efficiently. After all, marketers have been tearing out their hair for years trying to figure out how to craft that perfect subject line to stoke the interest of the recipient. Operating on the same principles of prescriptive analysis as mentioned above, AI’s algorithms can predict what email subject lines will resonate personally with a subject, and recommend subject-line options accordingly. According to Phrasee, which offers just such a platform, they make the bold claim that AI-generated subject lines outperform human-generated options 95% of the time.
And it doesn’t stop there. AI can allow for better send-time optimization, personalized images, greater email marketing automation and even impression predictions. Moreover, AI can leverage the data obtained from email campaigns into broader marketing analyses. Take Adobe Sensei, for example. This AI platform boasts that it allows you to work “better, smarter, faster.” What it can specifically do is take data from email campaigns in order to accurately predict customer churn.
This is just one of the many ways AI is facilitating conversions while personalizing the customer experience.
Social Media Authentication
According to statistics, 85% of U.S. consumers said they use social media, and over half of them follow brands on social platforms. It’s no wonder that social has risen to become one of the three foundations of digital marketing, besides search and content, and is now one of the principal ways brands communicate with their target audience.
Of course, these efforts are not useful if researchers are only following the behavior of bots. That’s the big chink in the armor of an otherwise optimal social strategy: sometimes the data you’re looking at is being juked by fake social media accounts. This is where AI comes in. Imagine artificial intelligence not eliminating the need for social media market research, but asssuring the researcher that they are identifying actual targets and actual social media comments. AI can also provide the researcher with the authentic data required to do their job efficiently which means no more blind alleys or wasted time.
Many businesses are now relying on Instagram to get the word out about their brand visually. Of course, engaging with an audience merely by tags isn’t the most efficient method. A business can track a third or so of all tags, but then they lose others and waste valuable time scouring their Instagram account searching for them.
That’s where AI-based image analysis comes in. With some three billion images being shared on social media every day, AI can help sort through these images and provide researchers with the most relevant posts that showcase the behavior of the audience they’d like to target. It can also help identify the mentions of their competitors, which serves as invaluable data as well.
Here’s an example. Say there’s a company that manufactures sport watches and they have an Instagram account with 20,000 followers. Maybe your job as a researcher is to look at all the tags in order to further define the audience. But maybe you’re only able to find the most specific ones.
If you were to use AI to power that insight, you’d be able to find close to 100% of relevant tags—even when the product isn’t even mentioned by name. Maybe it’s just a follower holding the watch up to the camera in a selfie. AI’s evolving power now allows it to visually decipher the logo in the post and categorize it accordingly.
Natural Language Processing
The ways that machine learning can help boost customer relationships goes well beyond analytics. Consumers are already interacting with AI in the form of chatbots in the customer-service sector. So how do we ease society’s anxiety about AI becoming a part of our daily lives? The one-word answer: audio. More specifically, voice and natural-language processing.
Language is a principal way humans communicate. So if we want potential customers to take these new technologies seriously, we need to meet them on those terms. That’s precisely why virtual assistants like Siri, Amazon Alexa and Google Home are only gaining in popularity, and why giant brands like Google and Microsoft now identify as “AI first” companies—because we’ve found a way that artificial intelligence can relate to the consumer.
Now, this will certainly upend the world of market research, but that doesn’t have to be a bad thing. Consider the benefits: it can be an efficient, less costly alternative to primary market research. It will eliminate reliance on useful but limited quantitative research tools like surveys and expensive qualitative tools like focus groups. This neuro-linguistic programming can further boost efficiency by using sentiment analysis to gather thousands (or even millions) of opinions a minute. Another added benefit is NLP’s ability to read countless documents at once, thus automating secondary research and eliminating the need for long hours scouring the web for info.
AI may in fact be evolving at a rapid pace, but that means it’s leaving more opportunities for researchers and marketers than ever before. These opportunities invariably come in the form of more efficient data gathering and more intuitive customer interaction. Those who focus on those areas will find they have no problem adapting to the “robot uprising.”
Ryan Gould is Vice President of Strategy and Marketing Services at Elevation Marketing. An expert search, social and content marketer, Ryan leads Elevation Marketing’s digital strategy department, helping brands achieve their business goals.
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