What is Digital Behavioral Intelligence?
In order to understand digital behavioral intelligence, first, one needs to understand behavioral intelligence.
And in order to understand behavioral intelligence, one needs to first understand emotional intelligence.
Emotional Intelligence (EQ) has been around for decades and refers to an individual’s understanding of their emotions and how those emotions influence their actions.
Having a high EQ allows an individual to also have a solid understanding and empathetic recognition and awareness of others’ emotions.
Emotional intelligence is internal – it happens inside people’s brains.
On the other hand, Behavioral Intelligence (BQ) is external and involves what people can see and respond to.
It is observable and requires an ability to recognize the impact that emotions have on one’s own behavior and the behavior of others.
To steal an analogy from my friend David Holzmer – “If EQ provides us with a slow-motion selfie, BQ plugs us into a real-time, live streaming video captured in 360 degrees.”
Behavioral Intelligence casts a much wider net in capturing the dynamic impact and influence of collective behavioral patterns.
Putting psychology aside for a second – Military “Intelligence” refers to any information about another group, organization, nation, or people that is useful in strategic planning or executing of military operations.
To quote Michael Taillard in his book Psychology and Modern Warfare…
“With the right kinds of intelligence about the actions and behaviors of others, one can not only deconstruct behaviors to derive their root causes, thereby allowing one to understand the intentions, motivations, and plans of others, but one can even predict the future actions that the person will take.”
That is a beautifully written segway into a new category we’re developing at ForMotiv called Digital Behavioral Intelligence, or DBI.
Digital Behavioral Intelligence
Digital Behavioral Intelligence (DBI) does exactly the same thing, but online.
Gathering Digital Behavioral Intelligence and analyzing users Digital Body Language helps companies figure out the root causes of their user’s actions, allowing them to understand their true motivation and intent.
Predictive behavioral analytics then allows us to analyze that data and predict the future actions that person, or people like them, will take.
Most businesses collect an immeasurable amount of data (intelligence). Data is at the core of every business decision today.
However, the available metrics used to inform business decisions, gain a competitive edge, and understand customers is limited, to say the least.
Page views, session length, and user flows is just the tip of the iceberg when it comes to data collection.
Not to mention, decisioning solely off of this data set could actually be harmful as it does not paint the entire picture.
Understanding user behavior is crucial when it comes to increasing conversion rates, engagement, retention, security, and revenue.
Only digital behavioral intelligence can inform you of your user’s digital body language, a necessary component of personalizing your online experiences.
The Importance of Digital Body Language
Imagine you’re interviewing for a new job and you just sat down with the hiring manager. How would you start? You don’t just ask about salary and benefits and walk away – if you do, you’re a lousy candidate.
If you’re a good candidate, you start a conversation.
If you’re a great candidate, you adjust, or mirror, the conversation based on the hiring managers body language.
If they lean in when you talk about your direct impact on a marketing campaign, but they look at the clock when you start talking about hiring a marketing agency to handle the workload, you’d (hopefully) go back to talking about your personal impact on your company’s revenue.
So, the question becomes, why aren’t more companies mirroring when it comes to their users?
Most companies rely solely on web analytics like Google Analytics or something similar to understand their site and forms performance.
Again, these companies are missing the bigger picture and it is likely having a major impact on their overall performance.
Analyzing traffic, site speed, and similar metrics could be categorized as vanity metrics.
How would you have any idea if they were finding what they were looking for?
You can look at site traffic as the new “follower count” for social media influencers…a vanity metric that doesn’t paint the whole picture.
If someone with 100,000 followers is only getting 100 likes on their posts, I’d highly suggest not paying them to post about your product.
If lots of people are on your website, great, but if they aren’t finding what they’re looking for, not great.
They are likely dropping off with a bad taste in their mouth and will never return.
As companies continue to look at metrics strictly through a Google Analytics lens, they’ll continue to make misinformed decisions.
It takes keen behavioral intelligence to really look behind the curtain and uncover the true experience and intent of those users.
How is Behavioral Intelligence used in forms and applications?
Industries like banking and insurance are undergoing a digital transformation, shifting from face-to-face to faceless interactions.
Looking at Google Analytics will show you that users are hitting the form and not pressing submit and converting.
One would assume the user is just playing around with the site and not engaging with the form.
But if you have behavioral intelligence embedded inside the forms, you can uncover previously unimaginable insights into their digital body language.
Did they fill out a few fields but drop off when you asked for a phone number or some personal medical questions?
How are users engaging the application? Did they fill out questions in the order laid out on the page or are a majority jumping around? Did they drop off on a certain question, regardless of how it is arranged on the page(s)? Did they continually hesitate on a question or correcting a question? Did they edit their income, e-med questions, or other important information? Are certain forms performing better than others?
All of this information is crucial when it comes to the user experience on that form.
Converting more high-quality leads = higher revenue, plain and simple.
But here’s the rub – you don’t want to let EVERYONE through as not everyone will be a profitable customer.
So where does that leave you?
The answer comes in the form of dynamic experiences for your customers.
At the very least, businesses should be aware and able to detect key behavioral cues.
Taking it a step further, the experience can and should change based on a user’s DBL, ‘responding’ to that individual user.
If there is a high amount of hesitancy on a particular question, this could signal confusion or frustration.
In that case, dynamically adding in a friendly FAQ or ‘More Info’ option or popping up a ‘Live Agent’ or ‘Click to Call’ option could help pull them through.
User experience is an obvious use case, but the impact of DBI goes a lot deeper than just converting users.
Imagine a bot is rushing through an application… Why spend all that time and money further qualifying what you (could) know is ultimately not an actual customer?
Instead, in that case, having a dynamic prompt to ‘Upload a Drivers License” would stop them in their tracks, save you time, and keep that money in your bank account.
Or what about risky applicants or fraudsters- both very hot topics in financial services today.
As I stated before, DBI can break down root causes, understand intentions, and predict their future actions.
Those future actions could be an application abandon, a profitable customer, or in this case, a delinquent payer, risky applicant, or potential fraudster.
Having this insight gives companies the ability to further qualify risky applicants, make smarter underwriting decisions, and ultimately increase profits and lower risk, overall.
Digital Behavioral Intelligence for Agent Oversight
Understanding your customers using DBI is important, but so is understanding your employees and distributed agents.
Maximizing the agent experience is quickly becoming a key area of focus for companies as competition is fierce and many options are available.
Attracting agents by way of slick portals, applications, and user experiences are on the rise.
The first step is getting the agents, the next step is monitoring those agents for performance, as well as risk and fraud.
While the most public and commonly known example of agent fraud is that of Wells Fargo, you can think of them as the Mark McGuire of banking fraud.
Lots of players used steroids in the early 2000s, only a few got caught, and only the biggest stars had their names dragged through the media mud.
It took a concerted effort, new regulations, and new oversight measures to get the rampant steroid issue under control.
We’ve witnessed a similar scene in financial services.
Now that banking and financial services are on notice, they’re (hopefully) taking proactive measures to make sure they avoid similar headlines.
Many companies sell through internal or external / distributed agents. While a majority of those agents are honest, not all are.
Having behavioral intelligence on not just customers, but the actions of employees and agents are more important today than ever before.
Collecting information on who filled out which questions, when, and from what device can make-or-break a policy under investigation.
With a full audit trail, similar to the “Revision History” feature inside Google’s Docs/Sheets, the ‘he-said-she-said’ guesswork is eliminated.
We’ve heard examples of basic form field manipulation, i.e. agents or brokers changing answers after customers submit applications to make them look more attractive to carriers & receive a better rate, allowing the agent to close more deals. Cha-ching.
Examples of agents creating fake Gmail accounts for customers, sending themselves DocuSign’s, signing them, and then approving those policies on the spot.
Premium avoidance, fictitious policies, and coverage sliding are all very common in insurance today and carriers need to smarten up if they want to avoid penalties, fines, and public shaming.
Companies spend billions to prevent fraud every year.
Much in the way medicine is turning proactive versus reactive, preventing fraud needs to take a similar approach.
Proactively signaling and reducing risk and fraud is a far superior method of prevention.
Digital Behavioral Intelligence can be useful in a number of ways – from user experience analysis to fraud prevention, there is no shortage of applicable use cases.
While a lot of seemingly obvious use cases point out negatives, it goes without saying that one can derive important metrics to discover positive outcomes, as well.
Profitable customers, increased conversion rates, or even simply knowing users are engaging inside the website or application exactly how you’d like them to can all be helpful.
Interested in learning more about Digital Behavioral Intelligence and how it can help transform your business, drop me a line! email@example.com