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Content Marketing & Sales Attribution In the Smart Economy

You don’t need AI to better understand the basic information about the state of your business. AI tools help extend the ability to analyze that data for hidden patterns and opportunity to improve. But simply knowing how many new contacts were engaged by sales team, how many calls and messages were shared with customers, and the current interest level among customers for each of your products is available expands management’s ability to exert control over costs and conversions.

That’s why we built these practical data points into the dashboard in the Gig Economy Group platform:

  • Number of contacts added across the network;
  • Number of distributor logins;
  • Number of distributor meetings scheduled;
  • Number of shopping carts shared;
  • Media assets viewed;
  • and more.

Sales attribution is the foundation of a well-run funnel and business. Counting up the cost and results of a sales campaign, its supporting marketing collateral and social distribution costs, to arrive at an understanding of how each dollar spent, as well as every action taken by the sales team, is the basis of a well-run business. In the world of machine learning and smart platforms, this data is the raw material used to optimize messaging and conversion, but direct-sales managers can view this numeric data themselves to see into and tune their funnel for improved results without AI assistance.

The GEG Dashboard delivers valuable human-readable metrics that sales managers and marketers can act on daily. (Sample data based on GEG app testing.)

Sales data is the meat and potatoes, machine learning is the gravy. You’ll want more gravy. We serve more meat and potatoes, too, frim the first day the system is launched.

Imagine starting the week knowing that new contacts are down by 5 percent or 10 percent or that scheduled meetings are up by 6 percent provides managers a starting point for actions to improve closing rates. Management can take action and immediately see if key activities change in the dashboard.

Real numbers

Using real-time sales activity data, a company can adjust production and inventory to lower costs in response to projected demand. This practical application of the data generated by well-defined sales processes developed at the outset of an AI project can be applied to a variety of ordinary human business tasks from Day One.

AI will improve recommendations — our initial customer data suggests overall conversion rates can be increased by 5 percent to 10 percent within weeks.

How much did a single content asset, such as a product video, was viewed by prospects? The question can be answered without AI assistance. Managers can see the results for a single asset, and how it contributed to conversion rates to the next step in the sales process, deciding whether the asset has performed to expectations. These data views support constant improvement in content development.

Where does the AI fit in? It uses the same data, examining correlations between messages, media, and engagement frequency, along with customer feedback (are they more or less interested in a product after viewing a video, for example) to propagate the messages and media that work best. Human managers will need to track the sales context in which each media asset is shared to ensure both human sales reps and the AI remain focused on the customer’s needs and personalize for the individual. Tools will help sustain a meaningful context as distributors and customers’ expectations change.

AI coaches your distributors’ creativity with personalized guidance that helps them adjust each presentation for the person sitting across the table. AI is an additional tool that coaches the distributor while management receives insights that allow better content investments.

Smart coaching

Ultimately, it is the manager’s responsibility to improve sales performance. The process begins by articulating every step of the sales process to understand which resources contribute most to closing a sale.

The data displayed in the GEG dashboard delivers more insight into the direct-selling process that can be used for daily decision-making. If, for instance, the field or an individual distributor are not making enough calls, sales managers can drill into the dashboard to understand how to coach the field for improved results. The AI features of the GEG platform help the field to personalize the messaging and presentation of data, yet it is the distributor who is the soft interface with the customer that captures the most important feedback to customer experience magic.

The combination of human insight and long-term machine-learning analysis of trends creates conversion lift. Alibaba, the Chinese online retail shopping behemoth, has found that personalization of its offers on its Singles’ Day — the equivalent of Amazon.com’s Prime Day — led to a 20 percent higher conversion rate compared to generic offers. In direct sales, management coaching can be blended with AI guidance to give the distributor better insight into the what will move the customer.

AI is ubiquitous and the most effective forms are delivering behind-the-scenes improvements that improve the customer experience. Using raw data and AI suggestions, sales and marketing teams have unprecedented access into the conversion impact of every asset and every rep. It’s a new era for sales accountability, one that starts every morning with a quick view of the state of conversion events in your sales network.

GEG surfaces important data is easy to understand and use in real-time, even before the AI gets to work. Do you have that information at your fingertips today? If not, we’d like to show you what GEG can do.

 

 

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.com 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.

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.

On-demand in small business: Four ideas for growth

Where is your place in the on-demand economy? Many workers and small businesses, including retailers, see the encroachment of Amazon, WalMart, and myriad other services as destructive. Yet media-enabled global brands are consistently challenged when engaging home- and office-based customers. The future of your business, whether a physical location or as an independent contractor, depends upon finding new niches where human expertise overwhelms online-only engagement.

Non-manufacturing businesses account for about 80 percent of the U.S. economy and are reported by the Institute for Supply Management as growing strongly for 97 consecutive months. Amazon, Uber, Lyft, TaskRabbit, Instacart and other services seem poised to steal business from local experts, but we think that by studying their approaches, small business and independent businesspeople will find greater revenue opportunities and a foundation for maintaining a trusted relationship with consumers. There are many new niches in the ever-specializing economy.

Last week, Uber announced beauty salon network bgX had become the first “business that has fully integrated with Uber for Business.” If you are seeking styling or a blow-out before an important meeting, “The platform will provide the convenience of having premium salon styling delivered directly to women at home, work or at a hotel.” The stylist comes to the customer if they happen to be in London, Paris, or Dubai. It’s a small footprint, but bgX could build geographic presence with time and marketing, adding cities with high concentrations of luxury styling customers.

Services consistently add greater value than other
sectors of the U.S. economy

Uber’s head of Uber for Business in Europe told the Evening Standard that 65,000 businesses have begun to integrate Uber services. Health services and elder care home companies pioneered the gig-sourcing local drivers to bring patients to appointments and ferrying retirees to an from shopping, events, and around town. Westfield Malls set up Uber transit centers in 33 of its malls last Fall. Yet, a survey last year showed that the majority — 73 percent — of small businesses used no gig services.

Likewise, Amazon extended its Whole Foods home delivery service last week. Adding San Francisco and Atlanta, as well as adding a Prime discount of five percent on Whole Foods purchase, the once virtual giant is developing a physical footprint in local markets. With Amazon Go stores prepped to serve walk-in-walk-out shoppers, potentially as ubiquitously as 7-Eleven does today, the Bezos machine is targeting the consumer on the go while catering to their home and office needs with Prime and Prime for Business memberships.

As a small business or an independent worker thinking about how to compete against these global brands, focus on where the human-to-human gap has opened as a consequence of automation. Logistics have been improved dramatically, but feedback, recycling, and recirculation of products all remain stubbornly local in nature. A salesperson is still the best way to capture feedback because they bring the ability to ask questions and report back non-verbal signals. This is where a massive opportunity remains for individuals in the gig economy.

Scale, surprisingly, is the reason the Small Business opportunity is growing. The delivery of services and products-as-a-service require deep personalization. Mass personalization will remain a matter of demographic or psychographic templates that must be tuned in the last-mile to engage the specific customer’s values.

The Minte, an apartment cleaning service in Chicago, demonstrates how small businesses can find and fill gaps by selecting a target market to serve better than national brands can today. The company identified apartment buildings as a market where it could rapidly lower the cost of service by increasing customer penetration in a single location.

“Once you’re in one building, all the others start coming to you,” The Minte CEO Kathleen Wilson told BuiltInChicago. “It really just exploded.” Call it “share of locality” thinking. Instead of simply thinking of gaining more of a consumer’s wallet, look to expand a business’ relationship with customers’ neighbors.

Word-of-mouth and local selling of these services don’t happen entirely online. People make the sale and pass customers along based on their satisfaction with a service. The focus on increasing Share of Locality inverts the marketing challenge. Small promotional and direct-sales engagements can kickstart a local on-demand business. If you are looking at the on-demand economy as a looming threat that will wipe out your local services market, study the gaps opening between big brands and local buyers to find a new niche.

  1. SMBs should position themselves as a local connector between global brands and customers. Uber, for example, has a massive local targeting investment that relies on its teams localizing and distributing marketing offers based on geotagging and artificial intelligence.SMBs have extensive insight into local demand and can tap into, for example, mobility services such as Lyft, Maven, and Uber, providing deeply contextualized local offers.One small business may offer Lyft rides to customers who want to shop at their location while another may choose to offer in-home delivery. Both, however, bring a local customer to the relationship with a mobility provider that can be mined for additional service opportunities. If a customer likes dinner delivered every evening, would they also like a housecleaner to come tidy up after the meal? Assembling these local services, consolidating them into a single point of contact and feedback for global brands, is a defensible position in the market.
  2.  Shopping destinations should consider aggregating delivery opportunities. Amazon has begun installing Amazon Lockers in Whole Foods stores, allowing shoppers to pick up online orders while at the store. Groups of retailers and service providers need to look at the businesses near them to understand where they can consolidate the delivery of goods and services. With improved logistics and retail management systems, a local store could become the destination for picking up a new product and receiving hands-on support and training for the consumer.Expertise is the rarest commodity. Small business is the most distributed approach to expertise delivery, which has been the foundation of consumer trust for generations. If your small business is isolated from others but draws regular customer traffic, can you use Uber or Lyft to “do the shopping” for a customer while they have their hair cut, their car serviced, or while they learn a new skill in a small training center attached to a local mall?
  3. SMBs and workers should focus on excellent service and enduring customer relationships. Today, gig work is treated as a commodity, and it results in lower wages as more workers join. However, consumers prefer trusted providers, especially for personal services. As the on-demand approach to work expands, small business and labor both need to leverage the trust they develop with local consumers in order to build their pricing power.Differentiation based on service level and trust will increase earnings. At the very least, a highly regarded local source of service or product expertise — the person who sold the customer their last three lawn and yard tools or the regular provider of the perfect massage — can earn more based on increased demand.Going further, the local expert service provider can follow the “breakage model” adopted by many companies, such as DropBox. They charge a little more for a lot more service on the bet that most of the services will not be consumed. A local SMB service provider, for example, could offer priority callback and service visits to “members” who pay a small monthly fee to jump to the front of the line when they need help.
  4. Tie into the on-demand economy and push the limits. Uber for Business, for instance, has extensive information about the routes and timing for deliveries but does not have a personal relationship with local consumers outside the Uber app. Like salon company bgX, look at what your business or yourself as a service provider can deliver and seek to be the local partner for on-demand product manufacturers and local mobility providers. You will find that there is no local sales interface to collect feedback from potential customers and expertise is unevenly distributed.Your ability to use multiple on-demand services is critical to success, so mix and match aggressively. Attack the problem of how to get a product from point A to point B, to onboard a customer to a new service, such as home security DIY installers who need to train customers to manage their security systems, or the need to efficiently deliver for hands-on expertise, whether a doctor, lawyer, auto mechanic, or any other person-to-person service.Small business and individual workers can take a robust part in extending services revenue, by tying expertise to products, fulfilling delivery, service, and post-purchase support locally, and thinking systematically about where value can be added in the on-demand economy.