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How Well-Documented Sales Processes Spur Sales Creativity

The best trapeze acts work without a net, and the results can ocassionally be disastrous when plans go wrong. Brands cannot assume their sales teams can work without a net, on pure intuition instead of using a well-documented sales process, without inviting the inevitable disastrous outcomes that result from poor planning. As the economy shifts to on-demand work arrangements, it is more important than ever to give staff a sales roadmap so that they can apply their experience within the brand experience to create even better outcomes.

New distributors need a sales roadmap, even if they plan to find their own shortcuts to success. In the fast-changing, high-churn economy in which sales organizations exist today, every step in the customer’s sales experience should be scripted in order to free salespeople to innovate smartly to deliver personalized experience. That does not mean that every action a sales rep takes should follow the script, rather the script is the grounding that gives smart salespeople the ability to improvise. Direct-selling compounds the consequences of poor planning because distributors often mix multiple jobs to earn a higher income.

“We don’t want to tell our sales reps what to do” are the most dangerous words in sales management. It’s a declaration of surrender to failure. A company without well-documented processes has abandoned its ability to learn and respond to the market. Now that content management systems can be linked to machine intelligence to track sales activity, even in individual customer interactions, a well documented sales process can improve rapidly based on customer feedback. As each distributor tries variations in language and order in which content is presented, the machine learner assesses the results and encourages or discourages that behavior based on sales results.

Change — a constant evolution of marketing messaging, sales process, and customer engagement is essential to achieving personalized experience — is the only constant in business today. Without a documented starting point, companies cannot learn how to improve from the responses customers provide to their collateral, their key sales propositions, and their marketing messages to create more personalized customer experience. The benefits of personalization are clear. It produces higher customer retention, increases conversion rates by more than 400 percent, and drives customer recommendation sharing.

A smart content platform, which blends content management and delivery with machine learning that tracks sales representatives’ experiments with different messages, can automatically test the changes that create improvements. Moreover, AI can spot messaging that fails to engage and cull content to coach salespeople to use new content that performs effectively. But none of these benefits are available without the baseline of a sales plan, against which new results must be compared.

Distributor retention grows on solid selling process

Documenting the sales process is first and foremost an investment in onboarding success. It provides talented teams the confidence to improve every step of the customer engagement. New employees consistently identify the need for clear guidance during onboarding and in daily sales activities. Without that guidance, new distributors are more likely to struggle when closing their first sales and to leave the organization before contributing to the company’s profitability.

Steven W. Martin of the University of Southern California Marshall School of Business, describes top sales professionals as firmly anchored in their company’s customer interaction strategy. It allows them to “tailor … sales pitch[es] to the customer’s needs” and creating emotional connections with the customer. Marin also points out that the structure of a customer experience allows top-performing salespeople to challenge the customer’s assumptions confidently. These intimate moments happen only in the context of a strong sales engagement, but they can be pivotal to getting a deal closed because the basis for honest feedback flows both ways.

A salesperson working within a known structure knows when to step outside the script. That is the human skill for which you are paying salespeople. When augmented by machine intelligence, a rep can quickly reshape a presentation or make a new offer based on customer feedback — data analysis delivers coaching the distributor in real-time and, as they innovate on the plan, captures the changing customer response to understand whether the improvisation by the seller is effective.

Brands that fail to inculcate their basic values and messaging strategy with distributors during the early steps in their career with the company squander shareholder resources.

If your sales leadership insists that the salesforce doesn’t need a plan, challenge them to provide data that supports their argument. You may surprise those managers by asking, and you will likely not receive a quantitative answer to the question. Intuition is untestable without a documented process against which progress can be measured.

Do not let your brand grope blindly for success without plan-based metrics that allow your team to adjust quickly to changing customer sentiment. Ensure that your marketing department has the data to act on by selecting key conversion events in the sales process, and hold everyone to the facts. Is your sales process documented to support rapid analysis of changing market and customer conditions?

 

Onboarding to Machine Learning: Mapping Sales Processes

Improving a sales process with machine learning starts with a straightforward assessment of the existing content, including video, audio, text, graphics, and training, a company uses to onboard a new distributor to its policies and practices. These first steps, which set the stage for confident selling by new distributors, are essential to improving sales success during the first two weeks with a new direct selling company. People who close their first sales within 14 days earn an average of 71 percent more than a distributor who takes just four weeks to complete a sale.

Sales and marketing leadership tackling machine learning for the first time need to break their existing onboarding practices and initial selling activities into steps, then organize those steps into collections that are expected to produce a specific result that can be measured. We recommend assembling a map of the onboarding, training, and sales support experience for new distributors, as their immediate success will produce immediate improvement in revenue and profitability results. Tier your product content in terms of 1.) Company overview and welcome programs and content; 2.) Selling materials and programming for distributor use; 3.) Deep product information, such as sales sheets or detailed product knowledge videos.

Break down the first month of distributor experience into:

  • Onboarding: Introduction to the company, its mission, and selling process at the overview level — what you most want your new enrollees to know on Day One and to have internalized by the end of Week One.
  • Prospect Development: This is the first, most important step for a successful sales enablement tool. Rather than explain how to use the contact management tools, get the distributor to work immediately on adding prospects and following up.
  • Product Knowledge Development: Ongoing and frequently updated, product knowledge and product-specific training.
  • Sales Skills Improvement: If there is sales training content that is not product-specific, such as coaching on how to follow up or present at a meeting, these programs will be useful throughout the entire distributor lifetime, not just as they become familiar with the company.

We suggest beginning with a list of all existing content. Write the title of each asset on a sticky note and, on a second note, the goal for the asset, such as “Create a sense of welcoming support” or “Establish product- and lifestyle-claims policy.” Place the two sticky notes, asset and goal for the asset side by side. Examine all the content related to onboarding to see if there are multiple assets seeking to achieve the same outcome.

As common goals are identified, cluster the content assets by the expected outcome. It is likely there will be several assets that drive to the same distributor goal, and these variations are natural places for a machine learning content system to start testing to see which content assets are most effective.

Introductory content, such as a generic welcome message and overviews of the company, should be separated from practical how-to content related to using tools and services offered by the company to refine distributor sales skills. The latter training content will distract distributors from mission-centric learning. For example, most direct selling systems begin with a series of introductory videos about the company, its products, and how the distributor can start to work its selling process. These videos set the stage for future training, but they have a narrow set of goals: To build confidence in the distributor that they’ve made the right choice of product or service to sell, that the company is reliable and supportive of their success. This is essential for winning younger distributors’ loyalty.

With mission- and policy-centric content organized into the first category, the next step is to organize each of your sales task workflows for use by the machine learning platform.

Each days’ distributor training activities during the first two weeks must have a goal, such as confirmation that the new distributor understands the basic value proposition and mission of the company or that they enter and start communicating with prospects. And each day’s activities should contribute to the next day’s goals — if on Day One, the distributor enters five contacts, Day Two should include follow-up activities and content that help convert those leads to a call, presentation, or online meeting.

Look for multi-day processes, such as prospect development and determine whether multiple assets address the same steps and issues. These are convenient reference points when thinking about how to shorten and improve onboarding programming, which can produce immediate improvements in distributor success. Sales process steps in a “What’s Next” machine learning tool allow the distributor to focus on doing sales work instead of learning how to use tools.

Once the Welcome and Onboarding workflows are complete and redundant content identified for testing, the organization of product knowledge and sales skills coaching content if there is any in the current asset library. These are content categories that can be populated over time, as well as licensed from training providers for integration with sales coaching machine learners, which can target sales training based on the distributor’s sales challenges. For instance, if they consistently add contacts, get meetings, but don’t close, the tool can direct the distributor to training videos about closing, getting commitments, and handling objections.

With a smart platform in place, a variety of training programs can be added to address your network’s training needs and to address individual distributor challenges. In the next installment, we’ll explore attribution modeling for machine optimization of each step in the sales process.

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.

Product Knowledge Is Retention Power

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.

 

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.