Using AI to Analyze Your Brand's Category
The customer journey is no longer a straight shot down the highway as it once was. Instead, it twists and turns between the many digital off ramps that, collectively, define commerce within our digital world. Gone are the days when shopping – whether for a pair of shoes, a new refrigerator, or anything in between – involved a simple trip to the local department store.
To facilitate the new, modern customer journey, brands must focus now not only on significantly greater competition and product availability but a variety of purchasing channels as well. Likewise, just as the digital landscape is constantly evolving, so too are consumers’ interests, tastes, and expectations. Brands can no longer focus solely on their own products, they must analyze their category's landscape as a whole.
To successfully navigate such an intricate and fluid marketplace, brands need the agility to effectively engage an endless variety of shape-shifting affinities. As we have said before, a non-linear customer journey requires a non-linear strategy for brands to compete within a given category.
Financial Planning Exemplifies the New Digital Journey
Take, for example, how far financial planning has evolved just over the past decade. It wasn't so long ago the financial planning process still relied on the notion of finding a trustworthy and reliable financial planner to assist you in establishing a sound strategy. Aside from choosing the financial planner themself, the customer had very few choices to make, typically relying on their local financial institution or representative for guidance that resulted in a lopsided relationship that left little to empower the customer base.
In recent years, however, financial planning has expanded by leaps and bounds thanks to rapid advancements in technological platforms that now place nearly absolute control in the hands of the consumer. From investment choices to highly sophisticated financial planning suites that can integrate retirement accounts, cash equivalents, insurance policies, and nearly all facets of a customer’s financial life, the result of this technology provides a concise and straightforward strategy that integrates AI-based modeling to replicate market volatility and life's inevitable curveballs.
Social media influence and forum sites only further empower the financial consumer, affording the ability to research the investment strategies, products and planning platforms that are most suitable to their specific needs. Online forums like Reddit and Bogleheads.org provide a more communal perspective, making it possible to have open, nearly real-time discussions with others to share insights, concerns, and questions regarding their investments, financial strategies, and general outlook.
This innovative concept holds especially true amongst millennials that place a high value on both peer and media opinions before acting on any advisor recommendation. In fact, a recent Deloitte study found less than 10% of investment choices made by millennials are done without first consulting with peers or media before acting on advisor recommendations. To that point, the investment services industry has been forced to rapidly adapt to the new customer journey paradigm simply to remain viable in these segmented and digitized times. What better way to do that than to understand the perspectives, concerns, and emotions being shared and expressed in the communities that are being consulted in the decision process?
Understand Your Customer’s Preferences
Truly engaging your target audience involves more than just facilitating the many different paths the customer journey can take but, just as importantly, also understanding the journey within a larger context. Drawing insight on entire categories and how your brand and products fit within those categories can reveal entirely new market or consumer segment targeting opportunities.
Likewise, tailoring your brand’s voice to best appeal to the specific consumer preferences exhibited across the breadth of an entire category can expand a brand’s perspective and illuminate different segments to pursue. As a result, a brand can personalize its message based on the wide-ranging insights it reveals by analyzing entire category's landscapes.
Such efforts would have been far too ambitious and resource-consuming just a handful of years ago. However, with the advent of machine learning and natural language processing (NLP), brands now have the ability to efficiently analyze online conversations within forums, blogs, and social media platforms to extract those all-important insights into product categories and the accompanying customer journeys. These valuable insights include brand and product occasions of use, product attributes, consumer perceptions, and consumer segment attributes like demographics, personality traits, and interests.
Case Study: Engagement Analysis in Financial Services
To place these insights into a real-world context, O360 recently conducted a landscape study around consumer investing based on discussions in forums on sites like Morningstar, Reddit and Bogleheads. Within that broader study, looking specifically at the college savings investment category revealed the consumer segments that were most engaged and why.
- Segment 1 – This segment is all about tax efficiency and maximizing tax advantages across retirement, mortgage and college savings
- Segment 2 – These investors are precautionary and want the peace of mind of knowing they can provide for their children’s education needs, even if it might trigger non-qualifying distribution penalties.
- Segment 3 – This is a highly pragmatic consumer segment that prefers to fund approximately 50% of projected higher educational expenses as a hedge to provide the needed funds while also minimizing the risk of penalties.
- Segment 4 – Finally, this segment is OK with the risk of overfunding knowing any money that might be left over within the 529 can be transferred to a different beneficiary, including future grandchildren.
With the O360 platform, we understand the demographics, interests, wants, needs, emotions and personalities aligned with each of these segments. Understanding the consumer segments across a category at this level allows firms to personalize their marketing efforts to whichever consumer segments present the greatest opportunity. No matter your industry, a similar approach can be utilized to infuse your message with a customized touch that is tailored to each target segment, leading to increased customer conversions and retention.
Consumer Engagement Analysis Within a Category
Analyzing online conversations concerning your entire category rather than just strictly focusing on your specific brand can provide an accurate gauge on how well the individual consumer segments are being engaged by your brand and your competitors. Given the highly segmented nature of the customer base, however, the inherent differences between the segments – particularly with respect to variances in conversational language – can be challenging to draw insight from the often nuanced conversations and reviews. Thankfully, NLP can greatly improve the process by revealing demographics and subtle characteristics like emotions and personality types based on that nuanced language used by consumers.
Such insight allows brands to analyze which occasions best lend themselves to conversions within a category. At O360, our innovative platform can reveal the specific consumer perceptions or product attributes that drive the occasions of use. Likewise, brands can also extract the particular product features and attributes that are most appealing to both specific consumer segments as well as an entire category.
Most Important Topics to the Category’s Most Engaged Consumer Segments
Thoroughly understanding engagement levels for each of the segments within your category is a critical first step in further developing a customized marketing approach. Once understood, you can integrate specific topics that are of most interest to particular segments, including product attributes, occasions of use, and others.
Again referencing the financial services industry, O360 also worked with a leading property and casualty insurance company to analyze the home insurance category. Beginning with online conversations within forums to gather product level insights, we analyzed the current competitive sets and marketplace alternatives to see how they coincided with both current and historical consumer needs and desires.
Afterwards, we also analyzed blogs and social media channels to provide foresight into product features, unmet consumer needs, as well as customer wants and desires, mapping them against whitespace opportunities to identify points of convergence with the various consumer segments.
By gaining a thorough understanding of the unbiased, unaided consumer conversations on these topics for the various segments – across all products and brands within the category – we are able to help create content that presents a far more customized approach for the individual segments. Such insights can be used to optimize content across a variety of channels, including email, website, social, and sales support, and serve as a foundation for all kinds of other initiatives.
Obviously, such insights and opportunities are of little use in extending to your brand if they remain strictly theoretical. Thankfully, with O360s Digital Landscape, brands can rely on our platform’s analysis to provide a bottom-up view of consumer conversations to discover and analyze every aspect of demand across entire categories. With the help of O360's Digital Landscape, the theoretical has become reality – and segment engagement will be much more impactful because of it.