With the recent spin-out and rebrand of IBM’s Watson Marketing platform to Acoustic, many marketers are reflecting on their current and future approaches to Artificial Intelligence. Acoustic’s messaging will likely resonate with marketers as many have been burned by a growing tech stack and are looking to regain focus. As marketers explore what AI can do to help them increase revenue, the research we’ve conducted at TOPO highlights three key considerations to have top of mind.
Centralized data is now a necessity
All information stored about prospects and customers’ needs to be consolidated in one place. Many are painfully familiar with different datasets in CRM, Marketing Automation, Analytics, Personalization platforms, and Product usage data. It is nearly impossible for AI to be intelligent without the right data. For IBM and other enterprises, using this collection of complete data provides the foundation for AI. This means that all learnings and insights from Marketing activities, chat, phone calls, content consumption, and even predictive data like intent should be accessible in one place.
The entire customer lifecycle must be tracked
In many organizations, Marketing metrics stop once Sales Development and Sales take over a qualified lead. This behavior can help cultivate two different sources of data with the stages marketing cares about in one system (e.g., Marketing Automation) and the actual Sales Development and Sales Process in another (e.g., CRM). Any siloed approach must be eliminated to seamlessly capture each step in the customer journey.
Many teams are moving to account-based strategies to better target accounts, close a higher rate of deals, and more accurately track progress through the customer lifecycle. As an account-based approach is adopted, understanding your ideal customer profile – those most likely to become high-value customers – and how to find more accounts like them becomes a critical priority. This is supported by an 89% rise in investment in intent data (identifying and predicting accounts likely to buy) technology in TOPO’s Account-Based Technology Report. This strategy helps you to segment your audience to target the right people at the right time
Plan for the long-term
AI does not happen overnight and requires people and technology to be effective. In some organizations, Artificial Intelligence creates its own version of a tech stack with dedicated resources – tools, data scientists, analysts, etc. The top tech challenge for marketers surveyed in TOPO’s Account-Based Technology Report was insufficient staff or resources. AI will require retraining, sound decision making (including trusting the decisions recommended by AI), and new systems. The report also found that Marketing Automation was adopted by 90% of organizations while predictive technology and intent data were adopted by 34% and 28% respectively.
Many marketers are waiting to see the promise and proof that AI can work for their business before making any widespread changes as there are already challenges with what they have today. However, aggregating data and tracking throughout the lifecycle will yield benefits with or without AI and can be started immediately.
As marketers, we’re always eager to embrace new technologies with promise and AI is no different. It will require a patient approach with tightly aligned internal data processes between all customer-facing functions, strategic resourcing and prioritization, and a commitment to business results over time. AI is already present in many technologies we use today and will increase in relevance as tools and platforms better integrate data from the entire customer lifecycle. Don’t expect AI to come after your job though. Decisions involving empathy, relationships, and similar life experiences will continue to be dominated by humans.