Why B2B Marketers Need To Use AI To Improve Demand Generation
According to The 2017 State of Digital Marketing Report published by DemandWave, almost half of digital marketers state that their number one objective this year is to generate quality leads. This is a 26% increase over their 2016 study, which may very well signify that marketers are finally putting a higher value on quality over quantity of leads. However, marketers must determine if they are doing all they can to ensure the leads they are producing are actually of the highest quality.
Leading marketers have long understood the importance of a buyer-centric demand generation strategy. They have taken the time to interview buyers, mine their data, conduct research into their buyer’s markets, create buyer profiles and document the buyers purchase path and the role that the many stakeholders play along that journey. While this is far better than what most marketing departments do, it may not be enough to truly keep pace with today’s sophisticated B2B buyer. In fact, the same DemandWave study shows that only 35% of respondents believe that “sales finds their lead scoring effective.”
As B2B buyers continue on down the road of sophistication and complexity, it is imperative that B2B marketers keep pace. One of the ways they can accomplish this is to integrate Artificial Intelligence (AI) into the development of their strategies. Here are a few reasons why marketers need to use AI to generate the highest quality leads.
Taking Advantage of Unstructured Data
According to CaliberMind, 80% of all data that exists in an organization is unstructured (records of chats, conversation logs, email content, phone recordings, etc.). Even the best internal team or external agency will not be able to sift through that sheer amount of that data to gain insights. The alternative? Using the only readily available, 20% of structured data for the purposes of demand generation that is most often found in marketing automation and CRM systems.
Although some data is better than none, if organizations are only tapping into 20% of their data, it stands to reason they only have 20% visibility into their buyers. As a result, this will limit the ability they have to truly engage with them along step of their buying journey.
AI enables organizations to get a complete view of their buyers, their path to purchase and leads to better engagement throughout by accessing not only structured, but unstructured data.
Static vs. Dynamic Insights
Understanding the buyers path to purchase is a must in order to get the most value from your demand generation programs. The more advanced marketing teams acquire this information by talking to customers, prospects and sales people, as well as tracking buyer behavior as best they can through their systems. This static approach is beneficial at a high level, but cannot respond in an agile manner when changes occur to a buyers purchase journey.
There are so many factors that impact the buyer purchase path, so therefore it is necessary for marketers be able to adjust in real-time to these changes. By taking a static and manual approach to charting the buyer’s journey, marketers limit their ability to respond quickly. However, AI provides the immense benefit of being able to dynamically view the purchase journey, identify any changes and, or additional buyer personas that may become involved.
B2B buyers are dynamic in the way they behave and buy, and marketers need to be agile as well to best engage them.
There Are Expiration Dates
Developing a demand generation strategy is no easy task. For most organizations, developing a buyer-centric demand generation strategy can easily take weeks, if not months to do it correctly. While building a solid strategy deserves the necessary time, implementation of the strategy can take even longer, as the need to update and create new content, facilitate websites changes and implement the right internal process can be significant.
I spoke with one VP of Marketing recently who told me that from start to finish, their company took a full year to develop and launch their new demand generation strategy.
While I have no issue with a program taking this long to launch given all the work that is needed, this does raise the issue of how strong are the insights that were collected if they are done in a static fashion? If a demand generation program takes a year from strategy, to implementation to launch, that means that organizations are launching a program with insights that are a year old. How much change has occurred with buyers and their markets within those 12 months? There is a good chance that some of the insights that were generated have expired or that new events have occurred that impact buyers.
AI enables organizations to prevent their data and information from expiring as it provides continual insights. If there is a solution that can dynamically update critical buyer data, why would marketers not begin to use it immediately? Do not allow stale data to negatively impact your demand generation programs when there are tools available that enable continuous insight.
Better Enables Campaign Optimization
Demand generation is hardly set it and forget it. Once programs are in motion, the most successful organizations continually seek to fine-tune their campaigns based on available data in order to drive more value and revenue from them.
Many organizations are limited to a historical view of their campaigns that then influence the changes they will make to their programs. While this is far better than nothing at all, companies often have to wait a certain period of time to collect enough data to make intelligent decisions. What’s more, depending on the outputs of this data, there may be a need to go back and collect more insight, which if done in a static manner only perpetuates the problems detailed above.
With AI providing real-time insights, marketers are able to make more informed and intelligent optimization decisions in real-time rather than rely on potentially unreliable historical data to optimize their performance.
Using AI to dynamically shape your programs and deliver at the buying stage of the customer journey will yield better benefit. How much better? CSO Insights showed a 5.5% increase on dynamic alignment versus formal (static) alignment. Clearly, using AI to better inform demand generation should be on every marketer’s radar, as we all want to utilize the best, most accurate data to have better connections with our buyers and drive better business outcomes.