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How AI-enabled content is different from traditional content management

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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.

Gig Economy Group’s AI-enabled content platform watches all the actions of all the sellers in the field. Our action-card interface suggests messaging text, allowing the seller to change the email text they use to, for example, share a media asset with a customer. Each of these changes is an experiment at the edge of the network based on the seller’s insight into customer responses to earlier steps in the funnel. They would be impossible in the fixed-content structure of scripted content workflows that don’t allow unanticipated deviation at any step in the customer engagement.

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.

AI-enabled content listens and responds to the rep, acting like a coach to help them present the best story that sells possible. If a unique twist on the selling process is successful with one distributor over a dozen interactions, the AI will test the change in other distributors’ suggested messaging, literally inserting the new language or re-ordering the presentation of media to determine whether it will work generally. These small experiments quickly prove or disprove the value of many changes while constantly refining the brand sales experience.

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!

Delivering Actionable Sales Process Analytics

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Sales managers must interpret and act on more data than ever. Since the appearance of the PC in the enterprise, the burden carried by sales management in every industry has grown heavier. Support roles, from the administrative assistant to accounting staff who helped with various aspects of reporting, have vanished from many organizations. Those jobs were taken over by software, starting with the spreadsheet, leaving managers with fewer people with which to consult and share ideas when making sales process decisions.

Personalization of the direct sales process was impossible in the traditional data reporting environment, but there is a change afoot. If your team is not listening to its market every day, it is falling behind competitors who do and as a result can deploy new targeted content to appeal to changing consumer preferences. Intelligent content management and sales coaching platforms provide coaching to sales managers, summarizing vast amounts of activity to identify patterns that can be applied to existing content and training libraries to deliver personalized customer journeys at scale.

After many years of growing data burdens, leadership can spend less time exploring data and more on refining the details of the customer journey. If an organization has mapped its sales process for machine analysis, each step a distributor takes with a customer becomes actionable data that signals to management how to adjust content and messaging for success. Intelligent content platforms look at past patterns, compares that history to current activity, and applies probabilistic analysis to the data to catch significant changes in customer sentiment early. Machine learning-enabled tools will also assist management with distributor training, engagement, and retention with insight into which salespeople are struggling and excelling, even before the close.

For example, a video shared early in the customer engagement may begin to perform poorly because the because market attitudes have shifted — even a phrase that has become a negative meme in social networks can change the perceived meaning of a corporate message if left unaddressed. The signal a machine learner sends focuses on the conversion expectations for the video. If customers start to express lower purchasing intent after viewing the video, the tool alerts management. It is not necessary to wait to see whether the prospect becomes a customer. The system can point out emerging misalignment of messages with a high degree of certainty and determine whether a change is significant rather than temporary. There is no need to hunt for what changed, the conversion data makes the emerging problem clear.

Sales and marketing teams can quickly review the asset to identify what changes are needed, produce a new video and release it immediately. Today, the signal is also much less noisy than in the spreadsheet era when outliers often stood out without context, leading to false urgency and unneeded content production expenses.

Personalization, without the noise

The rise of highly targeted customer messaging could drown an organization in data without machine learning to assist with separating meaningful changes in content performance from normal variations in a marketplace. Because personalization delivers stronger results, it can make heroes of sales leaders who anticipate and respond to changing market conditions.

Direct sales companies, which have typically relied on quarterly outcomes, not daily insights, to recognize which marketing and sales messaging work and which are misdirected, are used to building intimate customer relationships. If your company is ahead of that curve, it is better prepared to compete in the on-demand marketplace emerging today. If not, take a look at the retailers seeking to step into one-to-one in-home sales relationships with consumers.

Direct sellers that ignore the opportunity to personalize the one-to-one sales experience using media and targeted messages could lose customers to retailers aiming to deliver everything a consumer might want within hours. Amazon even has a key to many customers’ door.

Improved distributor coaching and resource allocation within a sales network in the mobile-first environment transforms the customer relationship. Personalization makes the customer the star of their own show, concentrating all of a brand’s resources of communicating consumer expectations back to headquarter and translating that into improved products and experience. A company’s response to customer feedback is essential to building customer trust and establishing shared values.

The same kind of coaching delivered to reps in the field through an app can provide sales managers insight in real-time into how their expectations and actual sales performance align or diverge. It is a practice every company is preparing to embrace, and the companies that succeed first will retain long-term advantages over competitors.

Once made, in-home relationships are tough to break, as direct sellers well know. Retailers understand this too after seeing foot traffic decline as ecommerce nears 10 percent of the total market.

Smart content now or, perhaps, never

The level of feedback available today enables individual communication with distributors based on their personal skills, personality, and product knowledge. Sales management can take a systematic approach to coaching, sending videos, training, or product collateral to distributors, and following the results conversion data the same day. After sharing a video about a product the distributor has not sold effectively, the platform can tell if their presentation improved based on customer feedback captured during the presentation. If distributors consistently over-estimate their chance of closing, the platform can also provide coaching and report to management that additional attention may be needed.

Intelligent content delivery is a window into every sales engagement. Gig Economy Group’s What’s Next approach to sales coaching tracks each interaction, suggesting content to share and analyzing messaging for terms and phrases that ignite customer interest. Positive changes can be propagated through the entire sales organization rapidly, with each new customer exchange testing the underlying assumptions of the management team to confirm strategic alignment and efficacy.

By matching distributor strengths to customer’s expectations captured through distributor feedback in a mobile app even the individual sales relationship can be tuned for improvements. As the data set available to a machine learning system grows, more sophisticated insights become available. For instance, an introverted rep could be coached to share more with an extroverted prospect or remain quiet and ask questions of another introvert.

In direct selling, content programming and messaging guidance has been considered less important than the one-to-one encounter between distributors and prospects. Rightly so, in the past, but that is changing as online becomes the primary venue for brand discovery by shoppers. With in-home selling investments by retail reaching record levels, direct sellers must study how content, salespeople, and customers interact.

The insights available at each step in the sales process can convert a prospect into a lifetime customer, right in their living room, where direct sellers already have the advantage over retail and ecommerce competitors. The alternative is giving up the home field advantage direct selling brings to the game.

See You In San Diego

Gig Economy Group and LifeVantage will be presenting at the upcoming Direct Selling Association 2018 Annual Meeting in San Diego, June 17 through 19. We look forward to meeting you at the event, where our team will be exploring critical questions about the future of direct selling. Schedule a demo or reach out to meet and talk at our suite during the event.

We would also appreciate your joining our blog team for a discussion at the event about the challenges facing the industry. We will be writing about direct-selling in the weeks before DSA 2018 and would like to include your thoughts in our reports. Send email to schedule an interview.

What’s Next Is Personalization

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Personalization of customer experience requires two investments: machine learning-based targeting technology, and; human intelligence to interpret customer moods and feedback, as well as curate the media and messages served up for sales use. One without the other will create an inhuman and untrustworthy customer experience that feels to both worker and customer like following rules instead of exercising their passion and fulfilling their needs.

No one wants to be automated, subjected to rigid rules that cannot change, but anyone dealing with lots of information can appreciate being helped by automation. The choice to be assisted by your company’s automation is the critical offer every future employee, contractor, and a customer will consider. The future will be decided outside your organization, by those who can make it a success. These are the personalization-readiness questions to answer in 2018:

  • Is your company’s sales team ready to change based on measurable feedback?
  • Are sales and marketing teams equipped with content and tools, including mobile apps and social network integrations, that help capture feedback that crafts a personalized experience?
  • Is your company organized around constant progress towards distributor and customer personalization?

“Digital technology makes the customer the star,” according to ZEITGUIDE, an influential trend-watcher in New York, and while stars need technology it is the audience they need most to achieve stardom. The What’s Next model, which serves the right content to a salesperson at the appropriate moment to close or move a sale forward, can be extended to provide unparalleled post-sales engagement.

Human interaction is the basis for turning each customer into a star influencer on behalf of the brand – these person-to-person interactions are where creativity and variations on machine rules invented by a human create the surprising experiences that customers remember and share.

Here is the essential shift of context necessary to achieve personalization with limited resources: Think of your marketing, sales, and support teams as the customer’s audience. Companies have tended to think of the relationship the other way, treating the customer as the audience. The brand’s job is to deeply understand the customer, reflect the customer’s desires through the organization, and deliver the fulfillment of those needs as “star treatment.”

Think of your marketing, sales, and support teams as the customer’s audience. The brand’s job is to deeply understand the customer, reflect the customer’s desires through the organization, and deliver the fulfillment of those needs as “star treatment.”

The star experience is based on a series of actions, literally what the expected next step in the marketing and sales funnel, laid out by company leadership and tested through interaction with distributors and customers. A rigid and unresponsive customer experience will always fail because every customer and all the sales and marketing people who interact with them brings different criteria for success. Every star is unique and wants to be treated as their own end, not simply the means to revenue.

The star treatment is a form of mass customization. Applying available content to telling a personalized story based on targeting factors. The next step in the evolution of on-demand markets will require breaking down content, processes, and the measurement of success into micro-steps that can be personalized more efficiently.

Rise of the Augmented Worker

The rise of the machine intelligence is widely seen as a threat to human employment. We see a new challenge for human workers, an increased focus on service and care, which will extend far beyond familiar caregiver roles, such as assisted-living for seniors and physicians’ assistants using AI to replace doctors in many clinics. Doctors are now freed up to spend more time with emergent and chronic care patients – they are not disappearing, just moving to a different level of caregiving.

The next generation of care-delivery roles will be the interface between highly efficient supply chains and customers. Market research firm IDC projects that the combination of customer data and artificial intelligence will create 471,819 new jobs this year, as people augmented by machine learning fan out to improve customer experience in novels niches, adding $1.1 Trillion in new revenue top the economy by 2021.

The business of caring will include marketing, which must understand and anticipate customers’ needs during pre-sales engagements, sales staff that modulate the delivery of marketing content and personal messages to the customer, and a wide range of post-sales services. For example, many direct-selling distributors provide personal training services along with the products they sell. Markets are fusing products, services, and human functions into a continuous customer experience in which the salespeople play essential supporting roles for the organization and customer.

Winning and keeping customers, not just conversions is will be the defining challenge in sales during the 2020s. Every company will need a process that preserves its brand and policies while supporting the flexibility required by customer-centric personalization.

Brand Consistent, Human Creative

How can a branded organization interact with a constantly changing cast of human contributors to their sales and service experience? Since the commercial World Wide Web was introduced in 1993, the rigidity of corporate boundaries has been under assault and C-level executives have agonized over finding and keeping the best talent engaged in a sea of mobile workers.

We suggest “What’s Next.” The idea is simple: Use the brand’s existing marketing content and sales processes to analyze what is effective and racking the variations introduced by individual salespeople during their interactions with customers. A machine learning platform trained to understand the process and measure how variations impact sales outcomes watches all marketing and sales activity to find the most effective variations. Successful variations on the steps are rolled into organization-wide best practices delivered through the brand’s marketing content and sales processes.

It is not necessary to throw away the playbook your company operates with today. By launching a new level of customer-centric care using existing marketing content and sales processes, an organization can minimize upfront investments to free more resources that can be applied to filling content gaps, upgrading and expanding sales communication channels – leading toward an omnichannel customer experience – and find the optimal sales/support-to-customer ratio to maximize average revenue per customer. The challenge is deciding to change from a long feedback cycle to a short one, a finger on the pulse of your market every day.

What’s Next can be applied from the first encounter with a prospective distributor by a direct selling company, extending the onboarding process into the pre-enrollment. For example, LifeVantage, which recently launched a new Gig Economy Group platform-based app for distributors, engages prospects through an app and, at enrollment, sponsors help download and install it on the new distributor’s phone.

LifeVantage is optimizing its sales interface through the app to address every prospect, customer, and distributor touch individually, based on its existing best practices. Incorporating distributor choices about which message to use with a customer at a specific part of the funnel provides the company with guidance about where to invest in new content, improve training programs, and increase revenue.

Start Before Day One

The most successful training programs begin before the employee’s first day and last months after many companies consider their hires fully onboard. At LifeVantage, the app allows training programs take over from the sales experience through the same tool the enrollee experienced as a prospect. Depending on their experience level, the new distributor can start with more or less brand and product training – it’s their option to skip ahead to the core work the app does, to manage the customer relationship. That feedback informs training program development.

On Day One, the LifeVantage enrollee enters and starts communicating with up to 10 prospects, substantially increasing the probability of a sales in the first few weeks. As those customer interactions become more specific, such as focused on a particular product, the LifeVantage app suggests additional product knowledge training to ensure distributor success.

Throughout the onboarding, the machine learning platform observes the distributor’s sales activity and compares it to the brand’s established processes. If the distributor ignored product training that, because of customer interest is becoming a gap in their sales ability, the platform suggests additional training.

The platform also helps to compose successful text and email messages based on phrases and words that convert well for other distributors in the network.

Sponsors and management can receive alerts about changes in one distributor’s progress, which they can address through one-to-one conversations, or to performance changes across the entire network. Working from a simple dashboard, marketing, and sales leaders can create new content and messaging suggestions, testing them in real-time and receiving feedback from the field within hours.

The outcome is a comprehensive, well-aligned worker-customer experience. The two roles, worker and customer, have tended to be treated as separate experiences, but in the era of personalization, when every participant can observe and comment on the values they expect to be realized by a company, worker and customer’s experience will shape the brand’s reputation.

See You In San Diego

Gig Economy Group and LifeVantage will be presenting at the upcoming Direct Selling Association 2018 Annual Meeting in San Diego, June 17 through 19. We look forward to meeting you at the event, where our team will be exploring critical questions about the future of direct selling. Schedule a demo or reach out to meet and talk at our suite during the event.

We would also appreciate your joining our blog team for a discussion at the event about the challenges facing the industry. We will be writing about direct-selling in the weeks before DSA 2018 and would like to include your thoughts in our reports. Send email to schedule an interview.

Product Knowledge Is Retention Power

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As companies like Best Buy add local service and home consultation, direct sales organizations must train distributors on every aspect of the products they sell to remain competitive. The personalized in-home selling trend will reach every corner of the consumer market over the next five to ten years, placing the direct selling one-on-one customer relationship advantage in mortal peril. Product knowledge training is the basis for improved sales, faster product and business process innovation.

But most companies struggle to keep their reps trained, let alone ingest the ongoing feedback from the field that can ignite higher revenue and profits. Too often leadership’s expectations are based on ageing practices that are obsolete in the era of cloud services.

As selling becomes personalized, mobile, and mission-based in the hands of values-driven generations, the tools needed to successfully mine the data created through these interactions are the highest priority for a sales organization. In direct selling, the imperative to gather and analyze feedback from representatives is rising in the face of aggressive retail investment in personalization, not to mention improving distributor retention rates in an increasingly mobile workforce.

Product knowledge is the foundation of customer engagement and trust. “87 [percent] of consumers said they would be unlikely or very unlikely to make a repeat purchase with a retailer that provided inaccurate product information,” according to Shotfarm.com, a Chicago content management company. Each sales rep who flubs a fundamental product knowledge question because they are selling outside their area of competence due to poor coaching runs the risk of permanently losing a customer for the brand.

Combining content management with machine learning to deliver personalized product training to salespeople in the field redefines the challenge of keeping product knowledge up to date. “Smart” tools assist in building product knowledge and coach salespeople toward the products with which they are most likely to succeed. As marketing, training, and sales content libraries grow, machine librarians will be poised to help distributors tell a consistently expert story about products.

Augmenting a sales rep with appropriate content and sales process coaching ensures a brand can deliver the right content to a curious prospective buyer at the right time.

Today, sales and marketing leadership is challenged to rethink the training process to accelerate sales conversion rates while building higher customer retention rates based on distributor engagement in the branded selling process. Every salesperson-customer relationship is unique and companies today must treat them as such. This is a new opportunity, one born of the information era and utterly foreign to traditional sales strategy that uses one training program across the entire company.

Starting with achievable expectations

It is not necessary to try to train everyone in an organization about every product in the same way. Instead, training is conceived as a personalized experience that addresses the specific learning and selling styles of the salespeople in the field. This groundwork lays the tracks to personalization of customer experience.

Tracking sales activity using automation turns organization-wide product knowledge training into a tractable problem. Since direct-selling representatives tend to specialize in niche areas within a brand’s product portfolio, targeted training allows sales management to fine-tune product knowledge investments. Knowing precisely which products a direct sales distributor is trying to sell, machine learning enabled content platforms can identify knowledge gaps and serve up training that addresses the individual distributor and their customer’s needs.

Instead of aiming for 100 percent product knowledge across the company, the platform allows leadership to treat product knowledge challenges in isolation, using the sales coaching process to move distributors toward complete competence in their area of interest. People in the field experience less frustration because they receive more information that is relevant to them, which leads to a higher retention rate among distributors. That product knowledge competence extends to the customer experience as distributors become deep experts who can answer every customer question quickly and accurately.

When great distributors stay, they keep their customers with the company.

Diane Valenti writing for the Association of Talent Development suggests managers develop “return-on-investment” expectations as a baseline for training investments. “Assuming that sales reps are applying what they learned, you can measure whether what they are doing is getting results using sales metrics that you already have in place,” Valenti said. “Don’t invent anything new.”

Direct sales companies can start out with the content and process they have today and modify it, rather than try to reinvent themselves from scratch. Existing training video, audio, and documents can link to assessments of how well a sales rep has learned.

As a starting point, marketing and sales teams in direct selling organizations can base assessments of distributor competence on individual sales success, not just the all-up sales results for the organization. By capturing more feedback from each rep, such as asking them review questions a part of a daily or weekly briefing delivered to their phone or having them record customer interest level after each conversation, leadership can move quickly to refine training programs at the individual content asset level to improve overall performance.  This investment leads to improved conversion rates and average revenue per customer as the likelihood customers will become dissatisfied due to knowledge gaps in the organization is reduced because each representative is well trained.

Resisting investment in training is costly. Ignoring feedback from reps can be deadly. The Center for American Progress estimated that organizations with poor training see $13.5 million in costs due to poor skills, employee disengagement and higher turnover. For a direct selling network with 20,000 distributors, the direct costs and lost sales could be as high as $270 million annually.

Product knowledge training based on extensive feedback and personalization is a source of product and marketing ideas, not just a means to sell.

The ideas captured by listening intently to reps responding to customer needs can be used to redesign products and improve the customer journey. Insight at the field level will determine which companies win. Boston Consulting Group research in 2015 found that fast innovators are more successful, bringing new features and categories to market more quickly to generate as much as 30 percent of revenue annually from new products. Survivors of creative destruction don’t eke by, they thrive.

Successful training based on knowing “What’s Next?”

The training process itself is the map to organization-wide improvement.  An attribution modelling strategy systematically allows a company to lay out its expected sales journey and compare the resulting training and sales feedback with initial assumptions to pinpoint content and training gaps. The steps in the sales journey become a template for “What’s Next” in the representative’s day long after they have complete product knowledge. The same information used to train a rep can be repurposed to support their selling.

Product knowledge training linked to sales success or the setbacks experienced by reps in the field is also a leading indicator of customer issues. Following up on customer conversations with training material related to the engagement keeps the rep focused on learning and providing even more feedback about a product’s perceived value.

Automation leaves managers more time for understanding feedback, rapid, intuitive analysis of sales data, and improved content programming and product development. They can deliver more of what the field needs: Guidance and better resources. A What’s Next-based sales platform managed by a machine learner can experiment with the content delivery process, analyze the impact of small changes on conversion, and translate the findings into new sales journeys, as well as mine feedback for delivery to the product team.

A content platform with machine learning keeps the information stream to the distributor concentrated on what drives sales success for one person and one product, or an entire brand with minimal human oversight.

By making product knowledge the fulcrum of customer engagement, with personalized training for the distributor to help them move to better outcomes, a direct selling company reinforce its one-to-one relationship advantage in the market. Ultimately, the What’s Next design anticipates the customer’s questions, identifying their needs to give the representative greater insight into what drives the sales decision for each prospect.

The question every sales leader must confront is: “Are you confident that your sales team knows everything about your products that the customer will want to know before buying?” The answer at each step is found in laying out what the expected next step toward a close and measuring for success after each engagement.

The 70,000-ft. view of sales results is no longer sufficient in the personalized marketplace; managers must use automation to move along with their salespeople at the edge of the network.

See You In San Diego

Gig Economy Group and LifeVantage will be presenting at the upcoming Direct Selling Association 2018 Annual Meeting in San Diego, June 17 through 19. We look forward to meeting you at the event, where our team will be exploring critical questions about the future of direct selling. Schedule a demo or reach out to meet and talk at our suite during the event.

We would also appreciate your joining our blog team for a discussion at the event about the challenges facing the industry. We will be writing about direct-selling in the weeks before DSA 2018 and would like to include your thoughts in our reports. Send an email to schedule an interview.