Amid the buzz surrounding AI (a Gartner survey in 2018 reports that “11% of marketing technology executives reported AI as their top choice as the technology that would have the most impact on their marketing efforts in the next five years”), business leaders may ask if AI (artificial intelligence) is really mature and valuable today for marketing and sales- and if so, how it can be tangibly implemented.
Table of Contents
- Is there such a thing as AI marketing?
- What type of AI Marketing actually works?
- What AI marketing tools are out there?
- Lead Scoring
- Maximizing the value of your AI-enabled CRM with data flow automations
- AI Lead Enrichment and Follow-Up
- Streamlining internal processes
- Integrating AI tools into your martech stack
- What are some practical ways to implement AI in marketing and sales at my organization now?
Is there such a thing as AI marketing?
According to McKinsey & Co., AI does currently offer real value for marketing and sales: “AI’s M&S value comes from improved customer experience, higher sales, and lower costs.”
Improved CX: Personalization, faster processes
Higher Sales: Improved segmentation and more informed decision-making, more accurate lead scoring and improved lead enrichment
Lower costs: Streamlining internal processes with AI-powered automation and scaling processes in an efficient way
What type of AI Marketing actually works?
Gartner research on personalization in marketing notes that “personalization isn’t a goal in itself; it’s a way to attain performance goals,” and that personalization designed to facilitate the customer journey (eg, messaging that walks the customer through the process and aims to solve problems along the way), is more effective than personalization designed to reflect the customer’s personal identity, past purchases, or values. With increasing concern over the collection of personal data, it’s not surprising that customers may actually feel ill-at-ease when confronted with a reflection of themselves in the automated customer assistance. This indicates that organizations would do well to focus on the power of AI in streamlining internal processes and improving overall organizational efficiency, and assisting customers as they progress through the customer journey, rather than on extreme customer tracking and hyperpersonalization.
What AI marketing tools are out there?
The shift toward cloud technology, which has reduced the need for server provisioning at businesses and led to a shift toward operational expenses (OPEX) rather than capital expenses (CAPEX), has also led to the proliferation of cloud-based SaaS applications and point solutions that each address specific facets of businesses’ operations. This means that companies are often working with a large martech stack comprised of numerous cloud-based applications and services that can handle facets of the marketing workflow.
Paul Talbot of Forbes interviewed Jason Heller, partner and global lead of digital marketing operations and technology at McKinsey, about the future of marketing in 2020. Heller notes that AI can be seen as 1. Machine learning used in personalization platforms. 2. Natural language processing, for example, using AI to assist with copy-generation, and 3. Image and video parsing to analyze images and videos, to “drive engagement and value.” Heller’s key takeaway is that “modern marketing is fundamentally about data activation to drive growth,” and that the vast array of technologies that are at marketer’s fingertips today make it easier than ever to acquire and derive insights from data.
Salesforce’s Einstein is a set of AI features for the Salesforce CRM that can perform predictive lead-scoring. Salesforce is especially powerful when integrated with the data warehouse and other applications and systems that power an enterprise. Salesforce reports the value of using an AI-enabled CRM, as well as the value of marketing automation: “The rise of marketing automation made it possible to track leads’ online behaviour and gather certain types of implicit information. Linking marketing automation to CRM meant that larger quantities and a wider variety of data could be analysed and compared, as processes simultaneously became more automated and streamlined.”
Maximizing the value of your AI-enabled CRM with data flow automations
Maximizing the inflow of valuable data to your AI-enabled CRM can improve your team’s performance on sales calls. Although hyperpersonalization can be creepy, customers do want relevant, personalized assistance on their sales journey. Sales representatives can provide this much more effectively if they have real-time insights into the customer 360 as they take calls. Some barriers to this may be a slow reporting process and lack of integration between the CRM and the data warehouse. If sales representatives are relying on .pdf reports, they reports will likely be out of date by the time they actually take the call, and if there’s ineffective integration between the CRM and data warehouse, they’ll be relying on the engineers to pull data for them- not exactly an efficient process. Organizations can address this with data flow automations that deliver in-context insights to representatives in the CRM to assist them on calls. Keeping the CRM data up-to-date also improves the quality of insights distilled by any AI features that are being applied to data in the CRM.
Routing leads is a time-consuming process, and human teams may find that they’re not able to respond to sort and respond to incoming emails at the pace that they’re coming in. Additionally, humans go home after work hours, but the emails keep coming. Organizations can automate the lead routing process using natural language understanding AI platforms, including Wit.ai, Luis, api.ai, to automatically create a support ticket for the issue or request described in the email.
Let’s envision a scenario, where you are operating the most popular resort in the Hawaiian islands. You have a small staff, but they receive hundreds of emails every day, requesting bookings or information about your resort. The AI understands the language in the email and picks out important information, such as 1. Are they requesting a booking, or information? 2. Do they want to book a hotel room or the ballroom? 3. What days do they want to book the selected room? Then, a ticket is automatically created. If there’s a lack of clarity in understanding the message, it’s escalated to a human worker.
AI Lead Enrichment and Follow-Up
AI can be used as part of an automated workflow to orchestrate lead enrichment and follow-up from beginning to end. The process begins when a team member encounters a lead at an event. Instead of awkwardly scrambling for their laptop to start typing in the lead’s name and contact information, the employee can simply photograph their event badge or business card, and text it to a Twilio number. The automation picks up the photo and sends it to Google Cloud Vision, which parses the image using AI, and sends the data to Clearbit. Clearbit enriches the lead data, and the automation sends it to Salesforce. Within moments, the representative gets a text with the enriched lead information and a link to the new Salesforce profile for the lead.
Streamlining internal processes
Using AI to streamline internal processes that support an organization’s overall goals but which are not directly involved in sales and marketing, for example, accelerating hiring processes by using AI document parsing to analyze resumes, running a tighter financial ship with AI and ML tools for parsing expense reports and improving invoice accuracy, and streamlining processes like competitive wage research, can lead to an overall increase in profitability, and improve the overall operational infrastructure that supports sales and marketing. Rather than focusing on AI marketing as an isolated area of innovation, business leaders can look to AI marketing as one facet of their enterprise automation and digital transformation strategy. To run an efficient digital enterprise, business leaders should be cognizant of integrating all cloud-based marketing tools into the enterprise application ecosystem.
Integrating AI tools into your martech stack
Ascend2 reports that “52% of marketers say integrating disparate systems is their top challenge.” As organizations introduce new cloud-based tools, from new applications to AI tools into their marketing stack, an effective integration infrastructure is key for maximizing the value derived from investment in these new technologies.
There are two layers that need to be in place to maximize the value of your AI tools: integration (iPaaS), to connect AI tools to the rest of your marketing and sales applications, and automation, to use the tools as part of business process automations and workflow automations that span multiple applications and departments. An effective platform can handle both iPaaS and enterprise automation.
What are some practical ways to implement AI in marketing and sales at my organization now?
AI can be a powerful tool for marketers, but the real value of any martech is derived from orchestrating the tool or system into automated business processes and M&S workflows that use data to maximum efficacy and empower sales and marketing representatives with the right customer data when they need it. Organizations can connect to AI platforms to augment the performance of some facets of M&S operations, and focus on structuring the enterprise as a whole as an automated system with enterprise automation.
Workato is an enterprise automation platform that can be used for marketing to streamline campaign launches and improve performance tracking, automate lead syncing from various channels into your marketing and sales hub apps, automate the delivery of insights on user behavior that signals an upsell opportunity, and improve multi-touch revenue attribution. To learn more, request a demo from our team.