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.
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.