How Decisional Intelligence increases MQL Conversions
As the need for a more streamlined B2B buying process grows, so does the requirement of data granularity in demand generation. Learning about your buyer’s specific needs and decision-making habits has never been more prevalent than it is today. The standard software buyer in 2021 is being pulled in multiple directions, resulting in a decline in attention spans. This directly affects your ability to generate demand and thought leadership, as you’re not only combating your numerous competitors, but also the buyer themselves. This creates an “us vs. them” mentality with your prospective customers, and that’s not a space any organization wants to be in.
This can obviously be a hot topic for some – data is constantly changing after all. So, we decided to put together a helpful webinar to walk you through how decisional intelligence can affect your MQLs, your targeted marketing, and eventually, your revenue. Take a look!
Decisional Intelligence vs Big Data in Demand Generation?
As it stands, big data might be the most common form of processed data management. This comes from the simple need and/or thought of, “I have too much data to be managed manually”. Taking a step further, big data can then be processed and assessed through analytics to find consistencies and help streamline business practices. So, if big data is so commonly used and widely accepted, why are there other data collection and management solutions out there? The simple answer is- big data isn’t enough. As your needs as a business leader grows, so does the need for more accurate and intelligent data. That’s where decisional intelligence comes in. The ability to learn and influence data through behavioral and historical insights. Another form of decisional intelligence can be attributed to predictive analytics, or the gathering future insights on refined data.
Collecting, Augmenting and Enriching Data
Now that we’ve covered the need for granularity in data, and the idea of gathering decisional intelligence, a reasonable question to ask is “what does this look like in motion?”. In a perfect world, you’d be able to gather the data needed for all corporate marketing initiatives and manipulate it to fit your specific needs at that time. However, the reality is that data you’re collecting often times comes in different forms, even if it’s the same “prospect”. The main reason for this is the sheer fact that leads change over time. You may acquire a large portion of data from either a paid or internal campaign, and over a short period of time, that same data will change priority and even become unqualified. Why is that? The short answer is the sheer fact that they were in a lower part of the buying funnel at the time of acquisition. The long answer is the need to augment and enrich your data as you acquire it. The value of a fresh database of prospects and customers is insurmountable. On top of that, it’s absolutely key to learn as much about your database as you can, in a timely manner. Why? Personalization. Leads are only truly qualified and unqualified when personalization is used in outreach across the organization. The only way to use personalization properly is if you’ve spent the time getting to know your data through data enrichment.
Understanding Your Target Audience
Yes, data enrichment and augmentation are important, but if you don’t know how to apply these activities to your target audience of buyers, then it’s all meaningless. That’s because, at the end of the day, being able to speak to your target buyers through demand generation is all that matters. You need to know what they want, how they communicate, where they gather information, etc. All of this information can be gathered through utilizing predictive analytics, intent, and decisional intelligence to collect and modify your data. However, you then need to take that information, and put it in terms that promote interactions with your prospective clients. That’s a lot easier said than done, but there are some key best practices you can follow to help you start dissecting your data and applying it to your content and marketing efforts.
- First and foremost, identify what your targeted buyer looks like. Then develop a plan to interact with them, and the people that influence the decision-making process.
- Segment your database by various metrics like geography, company size, industry, etc.
- Create personas that contain your targeted buyer, the database segments, and overall needs and challenges each persona might face. This will allow you to streamline your personalized outreach and focus on speaking relevantly to your customers.
Autonomous Intelligence (AI) for Demand Generation
As you begin to develop your growth plans involving personalized data from your target audience, it’s important to look at how you can continue to learn more about your customers even after they become a lead. Through AI and machine learning, marketing predictive analytics has changed how sales and marketing leaders manage demand generation data in their pipelines. You can now learn key behavioral trends from your prospects, and through machine learning, predict how they’re going to make a decision and when that decision will happen. Essentially ensuring you engage with the right leads at the right time. A mindset and challenge that was once fulfilled through intent data; predictive analytics has substantially increased the number of insights you can gather from one lead.
Final Thoughts on Decisional Intelligence
To conclude, we can see why expanding data capabilities through personalized and future insights is not only valuable but required for 2021 organic growth. It’s just not possible for a business to expand their solutions and promote year-over-year growth without proper data enrichment, augmentation, and an analytical understanding. Finally, it can’t be stated enough, but knowing how to communicate with your buyers is absolutely key, regardless of how it happens. At Demand Science, we not only offer the capabilities to generate high-quality demand generation leads that utilize predictive analytics, but we also focus heavily on the conversations and engagement you have with your clients. It’s important to us that a cohesive narrative is told so that each lead you receive can work their way through the funnel at an accelerated pace while also providing you with actionable insights. If you’d like to learn more, take a look at our solutions page here!
The Personalization for Lead Development Guideposted on December 19, 2020
How Sales Prospecting Can Influence Lead Generationposted on May 11, 2021
Are Your Lead Conversion Rates Above Average?posted on December 5, 2016
Lead Generation through LinkedIn: A B2B Guideposted on January 26, 2016