How AI-enabled content is different from traditional content management
We are often asked what is the difference between an AI-enabled content platform and the content management systems used by marketers today.
Briefly, artificial intelligence (AI) adds the ability to learn and adjust content programs based on the success or failure of a change to influence conversion rates. Traditional content management systems (CMS) can be scripted to perform feats of personalization but lack the capability to learn from changes. In the one-to-one sales setting of the home or direct-selling meeting, AI can track any changes in representatives’ sales messages and understand if they help improve revenue.
That’s a pretty dense and, we believe, concise explanation. Here is what it means to your organization:
- Traditional CMS systems provide effective scripted customer experience, but they cannot learn and improve without human intervention;
- AI-enabled content platforms can learn and even test changes to customer experience without human intervention;
- The in-home and one-to-one selling environment requires rapid testing and dissemination of novel messaging that converts to desired actions at each step in the customer journey;
- AI-enabled content platforms give distributors active coaching that captures customer input and improves sales messaging by personalizing each interaction, and;
- AI-enabled content platforms reduce management overhead by automatically testing and reporting results to sales and marketing leadership, who can make better-informed decisions about the brand message based on more customer feedback than a CMS can collect.
Content marketing does an excellent job of delivering programmatic content, but it fails to understand the changing context of the selling relationship. As selling moves from retail to online, as well as into intimate contact with the customer in their home using mobile services, contextual changes in sales content will be the key to satisfying personalized experience.
Fixed versus Evolving Content
Now, let’s dig into the details of the different approaches to optimization of marketing and sales messaging made possible by AI. The advantage with AI is simply this: It can measure everything going on in the funnel rather than just those actions your team chooses to experiment with and track.
Traditional CMS systems have achieved high levels of personalization based on extensive scripting that uses conditions, such as the customer’s most recent action or demographic data, to direct them down a pre-fabricated sales path. The customer experience can often feel rigid since the workflow can be changed only by a content manager. Decisions to try a new word in a campaign or a novel order of message delivery, for example, are driven from the top down and involve A/B Testing and other methods of measuring changes in business outcomes.
![The GEG Action Card Interface](https://i2.wp.com/gigeconomygroup.com/wp-content/uploads/2018/09/ActionCard.jpeg?fit=139%2C300&ssl=1)
From the traditional CMS perspective, changes made in the field to selling materials and order of delivery are unexpected and consequently unmeasurable. A machine learning service may be able to assess responses from customers using natural language processing, however, the CMS will simply report the new condition to a human user, who must decide whether it is significant and worthy of an investment in testing changes to the content delivery scripts.
From Content Marketing to Contextual Selling
Machine learning, the form of AI used by Gig Economy Group, can ingest any changes and, by tracking changes in known conversion events in the sales process, determine whether a reps’ use of a new salutation in their email communications, such “Hey, Friend!” or “I’ve got a secret to share with you,” translated into improved conversion.
![SaleJourneys](https://i0.wp.com/gigeconomygroup.com/wp-content/uploads/2018/09/SaleJourneys.jpg?fit=300%2C300&ssl=1)
Sales representatives should be able to adjust every element of their communication to address the person they know more intimately than the platform suggesting messages. This provides bottom-up and widely distributed experimentation that can surface not just better next steps, but also the potential for a new market segmentation strategy. For instance, if in selling a business opportunity a distributor finds that her business-interested contacts consistently want to try the product before enrolling, she can start a trial purchase workflow that the AI recognizes and tracks as a new path to a known conversion event. The result is many sales process improvements with less management overhead required.
With well-defined sales processes established during onboarding to an AI-enabled content platform, the tools will surface productive changes in individual representatives’ workflows, as well as signal to management when a rogue distributor is failing to generate sales because they’ve deviated too far from the brand message.
Are you learning everything your market is telling you? If your CMS is not able to understand new sales paths, you will be blind to the improvements that customers and representatives invent. And in a resource-constrained market, those lessons are the hardest to embrace if your content platform isn’t looking for unanticipated improvement.
If you’d like to learn more, sign up for a demo of the GEG platform now!