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LifeVantage: Machine Learning In Direct Selling

Seeing is believing for Sandy, Utah-based LifeVantage. CEO Darren Jensen presented the sales results of LifeVantage’s early implementation of machine learning at the 2018 Direct Selling Association Conference in San Diego, reporting that distributor retention is up 34 percent overall in its 2018 fiscal year, which ends this month. The reason is improved visibility into the state of the business with the ability to intervene with new content and messaging to the individual distributor.

“We can now see if people are getting stuck at any of the [steps in the sales journey],” Jensen said during the presentation. The company, a leading seller of nutriceuticals and beauty products, is Gig Economy Group’s first commercial customer. Although its machine learning tools have been available only for a few months, LifeVantage’s pre-launch analysis of the sales process resulted in rapid improvements in novice distributors’ time-to-first-sale and, by extension, retention rates and average revenue per distributor.

Instead of looking at the whole process “once a year” based on annual sales results, Jensen said LifeVantage now relies on leading indicators, such as the number of contacts being added by distributors as well as meetings and calls presented by distributors. “Now we can see deep into our funnel,” he added.

LifeVantage CEO Darren Jensen speaks at DSA 2018.

Planning for machine learning in its business brought LifeVantage management face-to-face with each step of its sales process, raising new questions about how to achieve the highest revenue and revising the company’s basic assumptions about where to invest. LifeVantage’s comprehensive review of its sales methods and marketing content has recast management activity to focus on tactical changes to messaging and selling process that have delivered continued improving results.

“GEG sat down with us to devise systems and technology to answer and resolve the sales issues we have,” Jensen said. The process, which involved quantitative analysis of almost a decade’s worth of sales data, revealed three key principles that govern decision-making:

  1. Accelerating the first dollar earned by a distributor is the most effective investment LifeVantage can make in retention.
  2. It is equally valuable to sign a new customer or distributor. Because 66 percent of distributors begin as customers, LifeVantage deemphasized the traditional focus on having new enrollees recruit new distributors. LifeVantage also found that customers stayed longer and spent more money than unengaged distributors.
  3. The speed to the first sale by a new distributor is critical to their long-term success. LifeVantage found that if a distributor makes their first sale within two weeks of enrollment, after a year they earn an average of 71 percent more than someone who takes just another two weeks longer to close a sale.

Taking the next step

Direct selling is poised to evolve, adopting greater transparency and digital tools to treat distributors as key partners in success, according to Jensen. As retail and e-commerce companies, notably Amazon, press to gain access to the home, direct sellers enjoy a unique, temporary opportunity to take a greater share of U.S. and global consumer revenue. Shaping each customer experience to address personal concerns and values is mission critical.

The addition of machine learning lets the company “deploy technology to be sure people are closing in the right way to establish a trusted relationship,” Jensen said.

An Action Card: The distributor has just shared a product video with a prospect and will be reminded to follow-up when the video is played.

For example, LifeVantage now focuses intense effort on getting a new distributor to close their first sale. Simply winning their first dollar in revenue increases distributor retention by 44 percent over the lifetime of the enrollee (see LIfeVantage image above, which shows the likelihood of a distributor placing a monthly order based on how much they earn cumulatively). To accomplish this, LifeVantage provides each distributor a free machine learning-enabled app that begins training and sales activity on their first day with the company.

The app, which runs on the Gig Economy Group platform, reminds distributors what they’ve shared with prospects and how to follow up through a customized set of “action cards” delivered to each distributor. Action cards can display training content, product knowledge programming, sales guidance, and relationship management tools so that the distributor is always ready to do What’s Next to succeed.

“The first network marketing company I signed up for was one of the most exciting things I’ve ever been part of,” Gig Economy Group Senior Vice President of Business Development Yak Gertmenian, who spoke with Jensen on-stage. “Two weeks later it started to wane because I couldn’t find anyone to help me. I got stuck in the What’s Next trap. I didn’t know what to do.”

In addition to training, action cards provide suggested content to share with prospects, recommended messaging ideas, and follow-up reminders. These cards sent by the GEG platform to each distributor based on their sales skills, communication habits, and, importantly, customized messaging flows for engaging each prospect based on their expressed interests and feedback from the distributor.

Existential questions

Direct selling now competes for distributors with many more options for side income, a challenge LifeVantage sees as life-or-death.

“The next economy is here,” Jensen said. “We are at a tipping point where [direct selling] can become a leading industry or become irrelevant.” He recounted a seeing a recent Facebook add for Shopify, the online commerce tool, that claimed to provide “the best side hustle” to make extra income. As the gig economy evolves, 30 percent of Americans have embraced added income sources, ranging from Uber to selling.

“We are competing for the “side hustler” with multiple industries,” Jensen said. He told his direct selling colleagues: “We need to compete with all these companies at a higher level.”

By embracing machine learning, LifeVantage has learned to customize the onboarding and training experience, helping to increase success when it matters most. The results have been rewarding. In 2015, only 26 percent of new LifeVantage distributors completed a sale during their first two weeks with the company. By 2018, sales in the first two weeks after enrollment reached 36 percent, a 38 percent increase overall.

Interestingly, the sales lift extends past two weeks, even though attrition soars after the first month. LifeVantage also reports that sales in the first month after enrollment has increased from 55 percent in 2015 to 67 percent.

Working from well-aligned principles, LifeVantage and GEG developed a sales process that has allowed LifeVantage to weather the dismissal of a third of the company’s sales force due to unauthorized overseas sales without a decline in revenue.

“Technology can you extremely resilient as well as position you for greater success in the future,” Jensen concluded. As machine learning runs daily, LifeVantage’s insight into their funnel is propelling ongoing content and messaging changes to improve conversion success.

In our next installment, we’ll explore how Gig Economy Group translates client business processes into measurable sales workflows ready for machine optimization.

 

 

 

Personalization Advantage In On-Demand Markets: Direct Sales Or Retail?

The economy is going on-demand, following consumers’ desire for immediate delivery of whatever they want. The sales landscape is erupting with innovation like Kilauea volcano, wiping out businesses that fail to adapt. The way out of the swath of destruction is personalization based on consistent content marketing and sales messaging. Is your company in the path of creative destruction or leading the way with technology to rapidly personalize messaging, test results, and share best practices across the organization?

Consumers have embraced personalization of sales experience, as well as product and services delivery to the home. They are also seeking more home-based work opportunities. More than 44 percent of Americans are adding side-work, or “gigs,” to enhance their income. More consumers welcome local expertise when considering a purchase and more people will be seeking part-time work. On-demand markets create both growth and distributor-development opportunities for direct selling brands. The flexible and in-home business model is becoming the norm.

Retailers, including Amazon, Facebook, and Walmart, are moving rapidly to bring the customer journey into the home, too. Amazon has begun deploying the Alexa voice infrastructure to facilitate in-home ordering, digital locks to provide secure home delivery, and, even, offer medical services. Facebook partnered last week with on-demand home services companies Porch, HomeAdvisor, and Handy to offer in-home services tied to products sold and delivered to the consumer. WalMart this week introduced Jetblack, a text messaging order service that will bring products to the customer’s home in hours in hours.

Direct selling and retail brands both face the onslaught of e-commerce, which is eroding the advantage of physical retail as pre-sales customer interaction shifts to digital devices. Trade and business publications frequently announce the end of retail, a claim that should be seen in context: e-commerce accounts for only 10 percent of U.S. retail revenue in 2018, according to eMarketer.com.

For example, Amazon reportedly “owns” 90 percent or more of online sales in home improvement tools, skin care, batteries, golf, and kitchen and dining accessories as of early 2018. However, as a share of the total market, Amazon converts only 10 percent of sales in these categories.

There is plenty of maneuvering room to counter e-commerce with personalized sales and service in the physical world. Resisting the change, though, will lead many companies into dead-ends. Sales experience is fragmenting due to the rise of technology, particularly mobile phones, and the consumer’s developing sophistication and dependence on social influence when buying.

Direct sellers and retailers alike will eventually follow food delivery, home services, and e-commerce into intimate relationships with the customer that start and end in the home. Direct sales companies cannot allow retail to get ahead in the race for individual customer experience. One-to-one selling remains a necessary part of the sales process.

The face-to-face advantage

Face-to-face selling is still alive and well, but it cannot ignore the digital personalization challenge. No longer will a single sales message work for every customer. Direct sellers, who enjoy the advantage of building on personal relationships, will need to craft their messages to deliver better customer experience than retail. Since retailers must first attract customers to their stories, direct-selling strategies are advantaged in the social marketplace. Distributors can develop friendships online to grow their business and forge strong local communities on Facebook, Pinterest, Instagram, and other social networks with the same level of investment of time as a major brand.

Source: eMaketer.com

The online threat, nevertheless, is existential for consumer products and services companies that fail to recognize change and invest to build personalized and one-to-one customer experience. eCommerce will reach 15.1 percent market share by 2021, claiming an additional $365.68 billion in revenue, mostly from retail stories.

Recognizing that they could be consumed by the digital lava rolling through Main Street in cities and town around the world, retailers are not standing still or playing golf in the volcanic smog. Retailers are leading the charge into artificial intelligence to win a personalization advantage, spending the largest amount of any industry, $3.4 billion in 2018 on cognitive systems to augment their online and in-store marketing, according to market research firm IDC.

The Boston Consulting Group reports that retailer expectations for personalization are very high. In a survey conducted during 2017 by the firm, two-thirds of respondents said they will see a six percent increase in revenue from personalization spending. Half of the respondent retailers with more than 25 employees said they were putting at least $5 million into the machine learning technology last year.

Both direct selling and retail will depend more on personalization to convert sales as mobile-native generations age and become the largest group of workers.

“Over 70 percent of retailers are trying to personalize the store experience. That’s never been higher,” Forrester ebusiness and channel strategy analyst Brendan Witcher told AdWeek. “The reason is because so many customers respond to it. We see nearly three out of four consumers responding to personalized offers, recommendations or experiences.”

Success starts before the sale

Direct sales’ challenge is to stay in front of digital marketing efforts by retailers, which can be accomplished by building best practices within an organization and disseminating them using automation. Pre-sales communication, starting online or in-person, must become a focus of investment to ensure messaging is consistent and relevant. Using machine learning, an enterprise content platform can analyze messages and propagate successful content and sales steps to sales representatives using mobile devices.

Brand discovery also increasingly takes place online. Direct selling marketers must develop campaigns that drive and qualify leads. Content platforms then hand leads off to representatives using automated sales process coaching to deliver all the context to present a personalized experience to the prospect. From the first to the last, every touch must reinforce the brand message to successfully close a sale and establish a long-term customer relationship.

Consumers today do more research, check facts and customer reviews, as well as depend on conversational confirmation of their buying decisions than any previous generation. Often, engaging with a brand, retailer, or distributor is the last step in the process. Marketers can respond with better pre-sales content that develops trust with consistent messaging through the entire customer journey.

Machine learning-coached sales reps can step into the digital engagement at critical moments to add the human element that establishes trust, something retailers cannot do during their sales process today. Feedback captured by representatives sitting with the customer gives the smart platform hints about how to personalize the experience, refining the suggested content to share and messages the distributor can use to move the sale forward.

“The key to closing deals is presales’ ability to shape conversations with the client to position the company’s solution as the ideal ones,” wrote McKinsey’s Homayou Hatami, Candace Lun Plotkin, and Saurabh Mishra in the Harvard Business Review.  “This approach is not about developing a ‘smoke and mirrors’ pitch, but rather investing the time to have a deep understanding of the client’s needs (met and unmet) and then highlighting those elements of the solution that can address them.”

The foundation for a consistent brand message begins with mapping every touchpoint in the sales journey, from pre-sales and discovery through content marketing and sales process steps. The “attribution modeling” process allows management to identify what it expects will happen at each step and, using a machine learning-content platform, rapidly test and revise messages. Instead of launching content one or twice a year, then waiting to see its impact on sales in quarterly or annual results, it can be adjusted as fast as software updates are today.

The speed of software is the new pace of sales in the era of personalization. Companies are beginning to adjust to this accelerated communications cadence, and the tools for in-home personalization are catching up to web-only interactions. The combination of digital and personal engagement is a breakthrough moment in sales.

Personalization is the path out danger for retailers and direct sellers that don’t want to wait for the lava of change to erupt under them. For now, the one-to-one selling community has a sustained advantage over retailers who must attract the customer to their stores. If retailers’ investment in machine learning and personalization goes unchecked, direct selling could fall behind despite their strong foothold in consumers’ homes.

Content In Context: Cultural and Generational Awareness

Five generations co-exist in the economy and they live in thousands of cultures. Digital technology has wiped out traditional boundaries while culture has become more influential than ever. If a company cannot overcome generational and cultural differences, it will be relegated to a short life with little revenue. Future business growth will bump into ceilings created by differences in values and communication styles more often than those resulting from limited access to markets.

One-to-one selling is uniquely placed to grow revenues by testing cultural differences using rich libraries of content remixed by salespeople using customer feedback and assisted by intelligent platforms. Personal interactions in direct selling are the richest source of feedback available in business, allowing direct sellers using the data to see through values barriers long before the competition. Retailers can survey consumers endlessly, but their insights cannot match the feedback captured by a salesperson sitting with a customer in their home or during an intimate online conversation – before, during, and after the sale.

Younger workers have established that they want a mission in their work, and frequently opt for less traditional rewards than their parents to achieve flexibility in their lifestyles. Just as when they make decisions as a consumer, Millennial and Gen-Z workers value experience above compensation in many cases. The first thing a direct sales company must do with the next generation of distributors is establish that the mission behind what they sell aligns with social and environmental goals of new enrollees.

The development of onboarding and training programming, as well as customer-facing content that will be presented by a salesperson physically or through virtual channels, are a minefield in which cultural and generational mistakes can drive down distributor retention as well as decrease lead generation and conversion rates. Unfortunately, many companies think of their communications strategy – their narrative – as a black-and-white problem when they live in an age of rainbow perspectives.

Well-articulated stories told by a company about who they are, what they do, and why they do it, are the foundation of a global multi-generational communications strategy. Success grows out of variations on core themes expressed in subtly different language that maintain authenticity. Think about the difference between Baby Boomers’ idea of “cool,” Millennial’s use of “savage” to mean the same thing as “cool,” and teens today who say “It’s lit” or “Gucci” to confer coolness.

Every cultural interface is a communications challenge, one that marketers and sales leaders can transcend with solid data about which messages perform their expected role in the sales journey.

Messages must be mixed by the sales representative, who uses corporate content like a disc jockey selects music, to deliver a personalized human experience to the customer in their home, a coffee shop, or a retail store. For the first time, they can do it efficiently using machine learning librarians that serve content in context during the training process, sales process, as well as pre- and post-sale to keep customers involved in the brand’s community.

Budgets don’t need to be broken trying to cover every possible angle on a story from the start. An intelligent content delivery platform using distributor and customer feedback allows management teams to make incremental investments to address new labor and customer opportunities.

Look beyond the format trap

Many organizations see the cultural challenge in the simplest terms, too simple for their own good. They believe one generation or geography favors a different form of communication than others. Often, managers will assert that only 30-second, 60-second, or two-minute videos are acceptable to audiences, when the average time spent watching video online totals 2.6 hours daily, just minutes below TV viewing time.

Beware certain conclusions. Test what distributors tolerate when training and examine customer fall-off within videos as well as whether they drop out of the sales process after viewing a content asset. Distributors in learning mode may spend hours with a company’s videos each day. Each audience has different expectations that can be mapped to understand what message and format to suggest.

Differentiate your organization from most companies that invest heavily in just one communication strategy, albeit delivered in many channels. Plan a content strategy that spans cultural differences. Leaders who think their people can consume information in just one way can fail to engage new workers and customers, particularly when values-based products and services are discussed.

“By making the same message available in multiple formats (thus increasing the number of times you communicate a message), you’ll ensure that you reach all workers,” The American Management Association wrote, for example, when explaining communication preferences. “Silents [born 1925 – 1946] and Baby Boomers [born 1946 – 1964] may appreciate verbal communication about changes in policy or procedures, while Generation Xers [born 1965 – 1980] and Millennials [born between 1980 and 1996] may prefer the use of e-mail, instant messages, or corporate broadcasts.”

Content libraries have swollen with documents, video and audio programming, interactive training, and myriad other formats because of globalization. Marketers struggle to keep up with the demands of a multi-national presence, but that investment is the only path to ongoing growth. New markets are established using content programming that defines value propositions and introduces direct sales reps and customers to new products or services.

Think of the emerging cultural challenge as being like localization of content, the practice of translating text, video, and application software into many languages. Having five, 10, or 15 versions of the same message in different digital and physical formats does not necessarily help a company communicate effectively across borders. The English versions of a message must be translated without offending important cultural sensibilities into 80 or more languages to address the major linguistic markets around the world. The translated messages say virtually the same thing, but with unique tone and style that fits a target market.

Content targeting is not just a matter of agreeing with the language and values of the distributor and of the customer, it must also facilitate their continuing conversations. Their personal relationship may be built on cultural or generational bridges. A smart content platform can assess the identity of the distributor and their prospect based on distributor-entered data and sculpt a set of messages that genuinely connect these people during a sale.

We’re different, and not

The reality managers face as personalization comes of age reaches beyond acknowledging differences in values, they must also recognize and build on cross-generational and cultural similarities.

For example, different cultures emphasize the importance of leadership as an achievement in work. According to a survey by Universum in 2017, Millennial professionals in Nordic countries are far less likely to want to become leaders in their organizations than their U.S. and Mexican counterparts. Work-life balance is a driving concern for younger professionals everywhere and so many say they avoid leadership roles, but older people see stress as a natural component of their day. Across generations, however, the desire to be part of leadership varies by only four percent, from 61 percent of Millennials, 61 percent of Gen-Z, and 57 percent of Gen-X.

Content assets designed to emphasize different aspects of the company’s values or product attributes can plug critical gaps between cultures and generations. These gaps must be identified through real interaction with employees and customers, in effect probing the sensitivities of target groups. Distributors using a mobile app can relay back to management qualitative data that augments quantitative feedback to help them judge where to invest in new content or adjust the sales processes.

Intelligent content platforms are ideal for this kind of data-driven content and sales management experimentation. New programming can be rolled out to a narrow target audience, tested and, if the content leads to better engagement or increased conversion, deployed more widely.

The cost of poor cultural fit within an organization amounts to between 50 percent and 60 percent of an employee’s salary, according to the Society for Human Resource Management. Poorly engaged distributors sell less and move on faster, both of which drag down profits.

Without a clearly articulated company mission, values, and policies, organizations have no basis for achieving a fit. They can’t explain themselves and there is no benchmark from which to measure cultural alignment with distributors and customers. We suggest the attribution modeling strategy, which maps the sales process step-by-step. That effort is the basis for beginning to engage distributors during onboarding and throughout their career with the selling network. It provides logical paths to content reuse in support of customer communication.

Having built the distributor and customer relationships on smart content management services, direct sales leaders can use the inherently social nature of the business model to go “viral” with market-defining messages. New geographies can be accessed through distributors who, for example, emigrated from a country that the network would like to test. Targeting messaging to these bridge distributors allows management to explore the limits of their content investment and build new programs confidently.

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.

Closing A Critical Gap: Marketing and Sales Alignment

The central role of one-to-one relationships in direct selling places unique demands on marketing and sales leadership. Together they can succeed spectacularly but misalignment reduces conversion rates, wasting valuable investment in lead generation and customer experience.

As sales practices evolve to emphasize pre-conversion communication and trust-building through mobile apps, direct sales companies can leverage their unique human connection with customers for unprecedented advantage over retail and online brands. Historically, however, marketing and sales have competed for resources within network marketing organizations instead of working together to establish and disseminate best practices.

Competition between marketing and sales teams opens a costly divide within a company that limits the ability to develop and share best practices. If marketing messages fail to move the sales process forward, valuable leads are lost. Sales teams in direct selling often rely on their marketing partners for training content, company messaging to distributors and, in many cases, sales collateral designed to convey overarching value propositions which are not communicated consistently during the sales process. Without iron-clad data to prove replicable sales success or that points to where conversions are lost, the quest for change can become futile.

Beyond creating discord in the messages prospects and customers receive, the struggle for dominance within direct selling companies hits the bottom line hard.

Organizations with Strong Marketing and Sales Alignment Outperform Their Peers in Current Metrics. Source: The Aberdeen Group

A lack of alignment between marketing and sales messaging results in 14 percent lower achievement of sales goals annually and lowers customer retention by 11.1 percent, the Aberdeen Group reported in April 2017. When sales and marketing collaborate successfully, Aberdeen Marketing and Sales Effectiveness analyst Andrew Moravick writes, companies “grow revenue at 64 percent greater rate” than poorly aligned organizations.

As retail and online marketers increase spending on personalization in 2018 by 54.2 percent year-over-year, according to technology market research firm IDC, direct sellers need to tighten marketing/sales alignment to keep up with the best brands in the world.

It is time to augment direct selling content and customer relationship management systems with machine learning, often referred to as “Artificial Intelligence.” These tools arm direct-selling distributors with the right content for a specific customer at the most opportune moment in their journey.

Customer-centric, mobile-first context is king

Content rules when it is delivered at the right time. Content without context, like a confusing value proposition, turns off the customer.

Sales has changed, placing a premium on providing pre-sales information based on situational awareness of the customer’s needs. As companies develop huge content libraries necessary to support a rich customer journey, machine intelligence can serve as a context-aware librarian that retrieves the message, video, or collateral needed. The salesperson’s intuition can blend seamlessly with a machine learning platform if the final choice is left to the human in the field.

In addition to targeting the customer’s needs, a next-generation direct selling platform requires awareness of the salesperson’s strengths, product knowledge, and relationship with a prospect. Depending on the level of trust established between representative and customer, different content and messages can save or close a sale.

Marketing and sales leaders should work together using an attribution modelling strategy when starting out with content platforms using machine learning. Harvard Business Review authors Werner Reinartz and Rajkumar Venkatesan write that the attribution modelling approach “allows companies to attribute appropriate credit to each online and offline contact and touch point in a customer’s purchase cycle, and understand its role in the revenues that ultimately result.”

Leadership can begin by identifying a single target customer persona, then mapping out their ideal customer journey and the rules for handling each critical engagement expected to move the sale forward. This exercise compels marketing and sales leaders to talk about the customer-salesperson relationship based on a mutual understanding of the company’s customer persona, the target’s needs, and established product value propositions.

The extra ingredient that transforms this work into an alignment tool is the use of measurable events within the marketing engagement and sales journey to establish accountability for each team.

Growing measurable best practices

A high degree of humility is required in the face of real-time reporting. Feedback from the field shines a light on critical content marketing gaps, as well as a faulty sales strategy. Organizations can use machine learning-augmented content platforms to move from annual or semi-annual content development and sales planning to a quarterly or faster pace to optimize their sales processes.

At first, the mapped process represents a collective but untested agreement. With the help of a machine learning algorithm that applies the rules to find, contextualize, and deliver marketing content that supports the sales process. Real-world feedback generated by salespeople in the field will tease out multiple customer journeys. After that a fine-grained range of personae can be addressed with targeted content, expanding the addressable market without high incremental content production costs.

When designing a target customer journey, the teams can start with an inventory of existing content and map it to key conversion points in the sales process to establish accountability for message consistency. Sales leaders can be confident that poor content targeting assumptions during the planning stage will be clearly visible in the resulting metrics while marketers will be able to point out how content is misused in the field. These trade-offs can energize the entire company.

The attribution modelling strategy also gives leadership the ability to assess how marketing investments impact revenue generation. Simple rules for attribution can be used by a machine learning algorithm to adjust messaging cadence, the order in which content is presented at key touchpoints in the customer journey. As distributors add their feedback about customer interest and objections through a mobile app, the algorithm can be enriched to deliver insights that drive an organizational emotional intelligence unprecedented in sales.

Prior to cloud-based big data services, the initial rules and data generated by executing the rules would have required predictive analysis to be useful, but a machine learning algorithm can accelerate and simplify the process for management.

Customer feedback drives rapid organizational optimization

As distributors choose different messages and adjust the language they use when communicating through a machine learning-enabled content platform, the algorithm watches and propagates the what works best to improve outcomes across the entire organization, from headquarters to the field. By testing relentlessly variations in the order content is presented, suggesting new text through email, SMS, and social interactions, sales and marketing leaders assisted by a machine learning platform can evolve best practices informed by actual distributor decisions.

Moreover, poor sales performers in need of more training, specific types of coaching or improved product knowledge will be identified more easily than in direct selling’s largely manual sales reporting process. An investment in content targeting exposes the opportunity to improve individual distributors’ sales skills, as well as enrollee retention and sales conversion rates.

Sales and marketing alignment grows revenue overall and keeps customers buying. The Aberdeen Group reported that “Best-in-Class” companies, which see consistent year-over-year reductions in the length of their sales cycles and improvement in company sales quota achievements, “have complete or strong marketing and sales alignment, compared to just 45 [percent] of All Others.”

Direct selling companies that embrace machine learning platforms must be prepared to iterate based on the discoveries of weaknesses in their initial, idealized process. The rewards are numerous, from lower training costs and higher distributor retention rates, growing revenue and long-term customer engagement.

As data accumulates, each customer engagement, in email, in-person, online, broadcast, and the phone is revealed to be more, or less, important than leadership expected. Content and messaging gaps will become obvious because conversion rate changes are immediately reported by the system.

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.

Can you train contractors without becoming a legal employer?

The gig economy is a powerful force in commodity service markets, such as driving or “ride sharing.” More sophisticated services that require training, which courts have repeatedly ruled put companies in the legal position of employer, creating liability and increasing costs, especially legal costs, will reshape the development of business tools. The evolution of software – it is “eating the world” – points to the solution.

Federal District Court Judge Michael Baylson ruled in mid-April that UberBLACK drivers are not employees of the company because Uber doesn’t exert enough control over their schedules and they do not have to report to Uber employees. The Uber app controls the entire engagement between UberBLACK drivers, who can work when they want.

The ruling treats the Uber app as a tool used by the driver to fulfill the contracted service rather than a system of control. While the case may go as far as the U.S. Supreme Court and be reinterpreted many times, this distinction is critically important to the future of gig work arrangements.

The Society for Human Resource Management summarizes the scope of control issue: “If the employer will rigidly prescribe the manner in which the work is performed, that weighs toward employee status. Hiring an employee would be the safer course of action. If the organization is concerned only about the final product and does not need to dictate how the worker gets from point A to point Z, an independent contractor may be the preferred approach.”

We need new tools to enable professional-level services, not just simple commodity services, provided by contractors.

Brands have extensively documented, constantly evolving business processes that contractors must be able to follow reliably to deliver a customer experience consistent with their value proposition. With driving from place to place, the problem is simple. Uber and Lyft coordinate three things: Drivers; Cars, and; Passengers. Getting a passenger together with a car and driver to reach a destination is a relatively simple process, though hugely valuable, as evidenced by the companies’ more than $40-billion gross revenues. Likewise, dog-walking, package delivery, and other simple logistical markets.

More complex business processes, such as a sales engagement, retail interactions, professional services such as medical or therapeutic services, however, require a form of knowledge that has not previously been embodied in a simple app, a tool rather than a scope of control. These new software tools require sophisticated inputs, the ability to ask questions or provide information based on the customer’s circumstances and personality, and in many settings, a great deal of unstructured data needed to deliver the experience the way the brand requires.

These interactions cannot demand training before the contractor begins work. Based on repeated rulings, that training imposes a system of control.

Instead, a competent contractor needs to be prepared with general skills that can be applied to using a software tool that guides them through the brand experience in real-time. This demands software developers deeply understand a brand’s business processes to:

  • Guide the contractor through the correct information to share. For instance, if a medical worker on contract talks with a patient, they may need to be able to explain a HIPAA-related document and share it in the form the hospital company requires.
  • Understand feedback from customers inputted by the contractor to suggest media assets, next steps in the brand’s sales process, and other facets of the customer experience to the contractor as they exercise their skilled work.
  • Validate that processes are followed, as well as collect relevant data needed to refine the process in response to customers. The rapid evolution of brand experience demands that this measurement take place, or the company will miss key feedback it needs. The contractor can be coached to capture this data but may not be trained to do so in advance.

This merely summarizes a complex evolutionary challenge for on-demand services. Gig tools will certainly evolve from commodity services to refined high-touch services, such as prepared food delivery or online human services like legal services or therapy, which can be significantly improved by a greater focus on process. The transformation is just starting. I

Scope of control is a changing concept. The more easily a trained human can respond to process-led software, the less likely that person is to be treated by an employee. By moving the process to the edge of the network, into the hands of a skilled human who is able to modulate a branded experience, brands, retailers, and professional services firms can reduce centralized costs and move more compensation to the human provider.

Process-based apps are the path to improved contractor experience and brand experience. It also has the benefit of being less likely to result in labor litigation. We need better tools to complete the foundation of a prosperous gig world where flexibility is the primary driver of when and how people work.