In the fast-paced world of retail, brands often find themselves getting caught up in the sheer speed of communication. The race to stay relevant is high stakes and ever-present, and in this rush, there's a ticking clock - because relevance, by its very nature, has a deadline.
Under such pressure, brands often scramble to push out content and establish connections, all in a bid to make an instant impact. However, in this flurry of activity, a critical element is often overlooked – nurturing those initial connections by way of demonstrating genuine curiosity in the customer or audience you’re trying to reach. Without this crucial step, the connection remains fragile and fleeting. So, how do you ensure that these connections not only last but also turn into loyal customers? It’s a question that virtually every brand asks itself when it comes to finding the “next best customer”.
For context, the way we define “next best customer” in retail marketing is an individual identified through predictive analytics and behavioral data as having a high potential for future engagement, sales, and loyalty. This approach focuses on prioritizing marketing efforts towards prospects likely to become valuable, long-term customers.
Below, MERGE delves into this topic, offering insights and strategies to help retail brands navigate this complex landscape and successfully identify their next best customer.
Understanding Customers Through Curiosity (and Channels)
When it comes to pinpointing how and where to acquire the next best customer for retail brands, communication channels play a significant role and curiosity can become an invaluable asset. The retail landscape is diverse, with an array of shoppers who engage in various ways. It's not a linear experience; rather, it's a complex web of interactions across different platforms.
Social media platforms, specifically, have emerged as key players in this dynamic, with many customers prioritizing these channels for their shopping experiences. To truly connect with customers on these channels, it's necessary for brands to delve deeper, to ask the questions that matter, such as, "Where do you prefer to connect?"
Failure on the brand’s part to ask questions that glean information about the customer and their preferences can result in sending the wrong kind of message. Take, for example, a woman who is reading a news article on a website. That news website may be where she is engaged currently, but it may not necessarily be where she prefers to connect. Without knowing the customer's preferences, the brand may end up serving content that's irrelevant to the customer, such as men's fashion to the female customer in this scenario.
On the other hand, if the retailer takes the time to ask, "Where do you like to receive information?" they might discover that the customer prefers to connect on platforms like TikTok, Instagram, or Pinterest, informing the kinds of messages the customers could be open to receiving. Ensuring that the target audience is following the brand on these channels can open up new avenues for connection and engagement, as well.
Additionally, data segmentation can provide valuable insights into customer behavior. By combining first party data with behavioral data, demographic and psychographic data to build out segments, it's possible to pinpoint exactly where the ideal customer audience are making purchases within different channels. This combination of direct questioning and data-driven curiosity help retail brands better understand their customers, identify potential connection points, and ultimately, find their next best customer.
Refine Strategies Through Test and Learn Tactics
The pursuit of finding the next best customer often raises intriguing questions for retailers. Brands that dare to seek answers, however, are the ones that pave the way for growth. An effective approach to unravel the next best customer mystery is to implement “test and learn” strategies, which provides the latitude for brands to fail fast, but also move forward swiftly.
These strategies involve probing various elements such as content, channels, timing, and even specific influencers. The goal is to test these variables, glean insights from the results, and apply those learnings to future initiatives. Unfortunately, many retailers fall short in this area, perhaps due to a reluctance to take risks and allocating enough resources and allowing enough time to truly ‘test and learn’ especially with shopping behaviors and habits changing more dramatically than ever before.
Yet, to navigate through this complex scenario, retailers must be willing to take risks and invest time and resources to learn from them. This can involve conducting surveys, researching emerging trends among Gen Z and Gen Alpha, or even experimenting with different approaches and media mix. These test and learn strategies need not be costly either; they can be inexpensive yet yield valuable information that can lead to customer loyalty and greater reward.
Forecasting Retail’s Immediate Future
Disruptive technology like artificial intelligence (AI), predictive analytics, augmented reality, and voice search are already shaping the way brands connect with their potential customers.
At MERGE, our work with one particular client involved utilizing a predictive model that was built in-house to help understand the impact of engagement across paid, owned, and earned channels. This model meticulously studied how customers responded to different types of content on social media platforms. By analyzing engagement rates, click-through rates, search behaviors, and other key metrics, MERGE was able to predict expected results based on media spend.
This model was entirely customer-centric and relied on a deep understanding of customer preferences and behaviors. In the end, the outcome led to the creation of content and other targeted outreach that was more relevant to individual customers, both in messaging and the prospective channels where that communication took place, leading to an increase in conversions and overall satisfaction scores. The success of this approach underscores the importance of curiosity and personalization in customer acquisition strategies.
Looking ahead, personalization will continue to be a key element in customer acquisition, as customers continue to demand more tailored experiences with brands and retailers. Brands that can deliver personalized content effectively are those that track and analyze first party and zero party customer data to understand specific preferences and behaviors.
The future of customer acquisition transcends mere personalization; it demands the integration and effective utilization of data from diverse sources to overcome the limitations of siloed information. By ensuring cohesive collaboration among CRM, brand marketing, store operations teams, and other relevant departments through interconnected tools, brands can deliver a seamless omnichannel experience. This approach, coupled with the leverage of emerging technologies and a focus on personalization, will not only help brands identify their next best customers but also foster enduring relationships with them.
FAQs:
1. How do brands measure the long-term impact of personalized content on customer loyalty and retention?
To measure the long-term impact of personalized content on customer loyalty and retention, brands often employ a combination of quantitative and qualitative metrics. These include tracking repeat purchase rates, customer lifetime value (CLTV), net promoter scores (NPS), and engagement metrics across digital platforms. Advanced analytics and customer feedback mechanisms are also integral, enabling brands to assess the correlation between personalized initiatives and improvements in customer satisfaction and loyalty over time. Additionally, A/B testing various personalization strategies can provide insights into what resonates best with customers, further enhancing efforts to boost retention.
2. What specific challenges do retailers face when integrating data from various sources, and how can they overcome these obstacles?
Retailers face several challenges when integrating data from various sources, primarily due to contrasting systems and inconsistencies in data format and quality. To overcome these obstacles, retailers can invest in advanced Customer Data Platforms (CDPs) that consolidate data into a unified customer profile. Implementing standard data governance practices ensures consistency and accuracy across all data sources. Moreover, fostering a culture of collaboration across departments encourages the sharing of insights and the development of a cohesive omnichannel strategy that leverages all available data.
3. What are examples of successful test and learn strategies that can lead to discovering the next best customer?
Successful test and learn strategies in retail often involve small-scale experiments designed to gauge the effectiveness of different approaches to customer engagement and acquisition. For example, a retailer might experiment with targeted email campaigns versus social media ads to determine which channel yields higher conversion rates for a specific customer segment. Another approach could involve varying the messaging or offers presented to similar customer groups to identify preferences and trends. These controlled tests allow retailers to iteratively refine their strategies with real-world data, ultimately leading to more effective methods for identifying and engaging their next best customers. Through continuous learning and adaptation, retailers can enhance their customer acquisition efforts and drive sustainable growth.
Looking to keep your brand on the cutting edge? Connect with our team of retail experts at MERGE!