The Tech Behind Social Selling – Year in Review

December 17, 2024

How Brands Are Using Shoppable Video to Drive Sales

January 2024 Issue By John Lietsch

In today’s digital age, video has become one of the most powerful tools for marketing and advertising. With the rise of e-commerce, brands are looking for new ways to make their videos more engaging and interactive, and shoppable videos have emerged as a popular, effective, and profitable solution. Shoppable videos are a type of video content that allows viewers to shop directly from the video quickly, easily and conveniently. By integrating shoppable videos directly onto a retailer’s existing e-commerce site, retailers are providing a personalized, interactive way for shoppers to obtain invaluable information, increasing engagement and conversion.

Some retailers and brands choose to convert their existing library of videos thus reducing the cost of creating a shoppable video and maximizing return on investment. Others choose to create shoppable videos from scratch, focusing more on content specifically created to entertain and facilitate shopping. Research has shown that video increases engagement, so it’s no surprise to learn that viewers spend 47% more time watching interactive videos and around 40% of viewers add products to their carts because of a shoppable video, according to a Lemonlight Inc. report. In fact, in January 2023 the same report shared that video accounted for 65% of all internet traffic, and recent reports claim that figure might be as high as 85% once 2023 numbers come in.

Nearly 80% of people surveyed by Wyzowl stated that videos give them more confidence when purchasing, while DemandSage reports that 88% of respondents claim that seeing a video influenced them to purchase a product or service. The optimal quantity of products is somewhere between two and five products to share in a shoppable video, but those with two to three products tend to engage audiences more (and not overwhelm them). Generally, shorter is better, and short form video has become more popular. A suggestion is to make shoppable videos one to three minutes long, but the sweet spot is often in the 30-to-60-second range.

Don’t forget, avoid keeping your audience waiting and keep your TTFP (time to first purchase) short. Make sure you highlight the products you’re wishing to sell, and let your shots run longer on the shoppable product. If you have more than one product, don’t blast through every product. Give each product their proper “seconds of fame.”

Shoppable videos are an exciting new tool for brands looking to engage with their customers and drive sales. By enabling viewers to shop directly from the video, brands can provide a more engaging and convenient shopping experience, while also gathering valuable analytics and insights. Surprising as it may seem, e-commerce accounts for less than 20% of total global retail sales, but its share has been increasing as retailers and brands leverage different technologies to make the online experience more interactive and more human.

 

How AI Can Change Your Social Selling Strategy for the Better

April 2024 Issue By Crystal Holtzendorff 

Throughout its history, the direct sales industry has gone through a series of changes akin to a roller coaster with many ups and downs. Now, the introduction of artificial intelligence (AI) and automation is throwing the industry through yet another loop. Advanced technologies are changing the strategy and methodology of direct sales—and it is helping fuel sales growth. In 2022, the industry grew 8%, accounting for $40 billion in retail sales, and for the next three years, the industry is expected to grow at a compound growth rate of nearly 6%. Technology is playing a significant role in driving this activity.

AI isn’t a new concept, but integrating the technology into existing processes certainly is. Large powerhouse direct sellers are finding challenges pivoting their processes to incorporate AI tools, while smaller companies are struggling to capitalize on technology efforts at scale. Before committing to specific AI tools, it is equally as important to first establish a strategy and set of best practices. Companies of all sizes and market share are investing in AI, and it is important that companies remain flexible and open to innovation. 

AI technologies not only open a door for direct sales platforms to better engage with customers and improve customer service but also help to create back-of-house efficiencies that improve productivity and streamline operations, ultimately supporting field leaders and their downlines.

Chat GPT and similar AI-powered chatbots are able to write a variety of content for affiliates, including blog posts and sales scripts. With some experience, affiliates will be able to train the bot to speak in their own voice or the brand’s voice to create personalized and targeted messages that resonate with prospective customers.

When adopting new technologies, many direct sales companies believe that they should develop proprietary in-house solutions, but that is generally the wrong approach. An in-house program is expensive and requires a large experienced staff to maintain. It is also difficult to upgrade and maintain as technology advances. Rather, companies should partner with a full-service third-party technology provider that can provide scaled solutions and experienced support staff from Day One. Outsourcing to third-party technology companies also helps direct sales companies avoid the pitfalls of tech debt, or outdated technologies that require a significant investment to either maintain or upgrade. In fact, some chief technology officers have reported that 40% of their IT balance sheet is dedicated to tech debt. Outsourcing to a third-party provider that uses cloud-based tools avoids this problem in the future, creating a technology program that can grow and adapt with the company.

Predictive analytics help affiliates make strategic and targeted decisions that drive more sales activity. Using historical data and machine learning, predictive analytics tools can model future behaviors and predict outcomes. In direct sales, the tool can target users that would best align—or shop with—a brand, and it can even pinpoint the products that will best perform with a specific customer.

Compliance software and digital risk management software are possibly the most important tools for a direct sales company when adopting AI tools. Affiliates are representing the brand when they are selling in public and social spaces, but the corporate office often has limited control to review posts in advance, and the manual monitoring of posts is time-consuming and daunting. When adopting new technologies, many direct sales companies believe that they should develop proprietary in-house solutions, but that is generally the wrong approach. An in-house program is expensive and requires a large experienced staff to maintain. It is also
difficult to upgrade and maintain as technology advances. Outsourcing to a third party is a wise choice in this case as well.

By creating a system of best practices, adopting the right tools for both the business and its affiliates, and forming the right technology partnerships, companies are able to gain the biggest benefits from AI today and into the future.

 

Leveraging Behavior Modeling and Data Platforms to Drive Business Growth

July – August 2024 Issue By Ben Dixon

What a year 2024 has shown to be. The social selling space and the markets around it have grown noisy with fierce competition for consumers’ eyes and attention. Consumers today have more choices than ever, and your ability to remove friction from your sales process for social sellers is more crucial than ever. NaXum’s last article in 2022 highlighted the power of deepening your sales pipeline data. Those findings, in summary, found that most companies fall short of their ability to compete in a meaningful way because the technology and systems they use to measure their social selling promoters’ behaviors only track the transactional data like sales, enrollments, cancellations, and subscriptions.

However, they fail to measure accurate leading indicators (like webinars viewed, videos viewed, samples consumed, face-to-face meetings) and the predictive actions that created the leading indicators (phone calls made, text messages sent, and social media content shared).

The exciting finding was that if teams expanded their vision to measure their entire sales pipeline—using the newest third-generation technology in the referral marketing space—from the first interaction with the social seller to the sale, they would see opportunities to remove waste and optimize. From industry benchmarks, even a 20% optimization across the sales process would double an organization’s revenue per active social seller.

One of the simplest ways to measure member behavior is to provide technology, such as back office systems, marketing tools, or mobile apps. Regardless of which provider you choose to move forward with, the key is to structure your systems and tools to “feel like” an experienced (and compliant) social seller sitting next to the newest person on the team, suggesting what to do next. Just as you would traditionally use training videos and compliance software to build relationships with your social sellers and give them a path to run on, the focus in deploying tools that model appropriate behavior is to take what your training programs would have suggested and build tools that “suggest” to social sellers how to post the way you desire.

Now that you’ve implemented platforms that give you data across your entire sales pipeline, you must create a cadence for taking action based on the data these platforms reveal. We’ve seen that the cadence with which a company reviews and adjusts its predictive data directly influences its ability to optimize and grow. In summary, each leader has the opportunity to be extraordinary. To win in today’s market, the decision comes down to doing the actual work to provide platforms that add real value to social sellers’ lives. Companies can then get accurate data on their behaviors and apply what is learned to continue to optimize and remove waste for each stakeholder involved.

 

Unlocking Algorithm Favorability on Social Media

October 2024 Issue By Scott Kramer

The way everyone interacts on social media platforms like Facebook and Instagram is shifting rapidly. Once, social media was a space dominated by content from people we know—our friends, family and connections. Sponsored content also had a significant presence, as brands used paid promotions to reach specific audiences. More and more, social networks are delivering what’s known as “suggested” content—posts from users we don’t follow or personally know but that the algorithm deems relevant to us based on our preferences, interests, and behaviors.

Historically, social media platforms were about staying connected—hence the term “social network.” Facebook and Instagram prioritized showing you content from your friends, family, and the accounts you follow. However, over time, user behavior has evolved, and these platforms have begun to place more emphasis on showing you posts from accounts you may not know personally but might find interesting. “Algorithm favorability” is essentially about optimizing your content so that the platform’s algorithm considers it worthy of being pushed out—either to your existing followers or to new potential audiences through suggested content. As algorithms become more sophisticated, they rely on a complex set of factors to determine what gets shown, to whom, and how frequently.

To understand the kind of content the algorithm prefers, let’s use an analogy from television. Think of a 30-minute TV show. Out of those 30 minutes, roughly 22 are dedicated to programming, while the remaining 8 minutes are reserved for commercials. People tune in for the entertainment, the storylines, and the drama—the 22 minutes of programming. This is the “22/8 Rule” of content creation. Aim for 22 parts of valuable, editorial content for every eight parts of promotional content. By focusing primarily on creating value for your audience, you’re more likely to get your posts boosted as suggested content and stay in favor with the algorithm.

Social media platforms are ultimately driven by user engagement. The more a user engages—by liking, commenting, sharing or simply spending more time on a piece of content—the more favorably the algorithm will treat that post. Editorial content that focuses on entertaining, educating or enlightening naturally invites this kind of engagement because it aligns with what people come to social media for in the first place. Algorithm favorability is not an impossible mystery to solve. It’s about offering genuine value, being authentic, and understanding the balance between editorial content and commercial messaging. Embrace the power of editorial and let the algorithm work for you—not against you.

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