AI marketing involves leveraging artificial intelligence (AI) concepts and models to execute strategic marketing campaigns that achieve business objectives. Iterable’s AI Suite empowers marketers by providing them with the tools to gain insights, automate tasks, and enhance customer experiences.
As AI technology continues to evolve, marketers are likely to explore new and innovative ways to leverage it for a competitive advantage in an ever-evolving digital landscape.
Let’s delve into one of Iterable’s AI Suite features, namely Brand Affinity, and explore how it can reveal valuable insights for marketers to understand their share of voice and market share.
What is Share of Voice?
Share of voice (SOV) can often get confused with share of market (SOM), so before we get into Brand Affinity, we want to give a bit of background on SOV. SOV is a marketing and advertising metric that measures a brand’s presence in a specific market or industry in relation to its competitors. It quantifies the percentage of the total advertising or promotional efforts within a particular space that a particular brand owns.
SOV is often expressed as a percentage and is calculated by dividing a brand’s advertising spending, media coverage, or overall marketing presence by the total advertising spending, media coverage, or marketing efforts in a given market. A high SOV indicates that a brand or company is dominating the advertising or promotional landscape within its market, while a low SOV suggests that it has minimal visibility compared to its competitors.
Understanding share of voice is essential for brands to assess their market presence, measure the effectiveness of their advertising campaigns, and make informed decisions regarding their marketing strategies. It helps in evaluating a brand’s competitive position and can be a valuable tool for strategic planning and competitive analysis.
Now, how does this differ from SOM? Well, according to B2B Marketing Report, the SOV Principle states, “Brands that allocate a higher Share of Voice (SOV) relative to their Share of Market (SOM) tend to experience growth (assuming all other factors remain constant), whereas those with a SOV lower than SOM tend to see a decline.” A greater SOV implies greater potential for expanding your SOM.
Key Principles of the Share of Voice Rule
1. Balanced Branding and Performance Marketing
Achieving an optimal SOV and market share in marketing involves striking a balance between long-term brand building and short-term sales-focused performance marketing. A well-rounded marketing strategy typically allocates roughly 50% of the budget to branding and 50% to activation activities. Balanced marketing tends to yield 4x better performance compared to solely focusing on short-term, performance-driven strategies such as lead generation.
2. Grow Engagement Within Your Customer Base
Targeting only highly-engaged customers may not effectively contribute to your SOV. To enhance your SOV, concentrate on expanding your customer base through reactivation campaigns, referral programs, and engaging with low-engagement users.
3. Optimize Mental Availability
Successful marketing campaigns prioritize establishing “mental availability,” where the brand effortlessly comes to mind during purchasing decisions. This can be achieved by creating emotional connections with customers and prospects through branding and informative lifecycle campaigns.
Now, let’s explore Iterable’s Brand Affinity and how it aids marketers in comprehending their share of voice and gaining insights into better customer engagement.
Iterable’s Brand Affinity and Share of Voice
Brand Affinity, at its core, offers a comprehensive assessment of engagement across all messaging and calculates an affinity score based on how users engage with your messaging. By incorporating additional data, such as conversions, revenue, and behavior events, marketers gain a deeper understanding of the overall attitude their customers have with the brand.
This is where the Share of Voice rule becomes relevant. While a customer may initially have a negative Brand Affinity score in Iterable, a marketer can dig deeper to uncover insights that enable more targeted segmentation and campaigns, ultimately driving engagement and revenue. This also allows marketers to ensure they are balancing brand and performance marketing.
Layering Behavioral Insights With Brand Affinity for Deeper Personalization
Consider a segment that, based on their engagement data on promotional campaigns, has a negative affinity score in Iterable.
Upon pulling in and analyzing purchase behavior and revenue insights, a subset of these users is found to make purchases, indicating that the brand is top-of-mind for them. This presents an opportunity for marketers to engage with this micro-segment in a personalized manner, such as expressing gratitude for their loyalty or launching referral campaigns. These insights also unlock opportunities to leverage additional AI features like Next Best Action, Copy Assist, and advanced A/B testing.
By looking at additional insights when considering Brand Affinity, you as the marketer will have a better understanding of the behaviors and actions your users are taking as they interact with your brand. You can use this information to create micro segments and, from there, can send each small segment highly personalized communications to strengthen your relationship with each customer. Negative affinity, as highlighted, isn’t the end of the road—it’s the beginning.
Here are some additional use cases for neutral or negative brand affinity segments:
- Send thank you campaigns to negative affinity customers who purchased but have not interacted with messages. Use Copy Assist to iterate on different messaging options.
- Test different messaging and copy with inactive audiences using A/B experimentation to help entice and improve engagement rates
- Trigger a reactivation workflow when a user changes to a negative affinity
Iterable’s Brand Affinity, within the AI Suite, can significantly enhance your understanding of SOV by processing and analyzing data at scale, providing valuable insights, and enabling data-driven decision-making. This understanding allows marketers to balance their brand and performance marketing initiatives while expanding the active customer base through the testing of messages to customers with an initial negative or neutral brand affinity score.