Today, marketing success is developing winning customer-centric experiences. That’s why Voice of the Customer (VoC) data has grown from a nice to have to the backbone of measuring and managing the customer experience.
However, VoC data is always leveraged to analyze the experience after the experience has occurred. Also it is a dataset that is a small sample of the total population of visitors that visit your site. Therefore, the effectiveness of this rich, customer-centric dataset would be most valuable if leveraged to create individual experiences in real-time. Marketing is fuelled by data, but VoC data is oddly absent from the marketing technology ecosystem.
In this post, I will demonstrate how VoC experts can bring their VoC data into their real-time marketing systems creating unique and powerful customer experiences.
Data is wagging the marketing strategy
Today, digital marketing facilitates the execution of one-to-one marketing strategies versus one-to-many strategies. We now have mechanisms to efficiently offer personalized content but the tactics used to create more personalized experiences is limited by the data marketers have to work with.
At the moment the only data streams that are available to marketers at the individual level is behavioral data, from which marketers can inferred meaning, or explicitly known data, which marketers get from their CRM or other email capture sources.
Digital marketing strategy doesn’t often leverage digital Voice of Customer data (VoC) despite its rich customer-centric content, primarily because the data is only sample data and doesn’t move at the pace of digital marketing. But this can be overcome by leveraging recognition technology, as we will see later.
The data available should not dictate the marketing strategy
Behavioral data has been powerful but has led to issues wherein marketers infer meaning from behavior and create the wrong experience. Or they create simplistic strategies like showing you the shoes you just looked at. This creates the notion that consumers are been tracked without the value of the experience necessarily increasingly. (To read more about this check out Duff Anderson’s blog post – Retargeting 2.0 – Leveraging First Party Intent)
Similar issues occur with explicitly known data, where marketers skate too close to concerns of privacy or incorrectly use personal data or emails. In today’s digital environment, marketing strategy has been built around the data available instead of trying to create the data to support delivering messages and experiences based on intent. (To read more about doing personalization based on intent check out my blog post – Personalization is about the purpose, not the person)
Strategy needs to flow from strong consumer understanding
In the previous era of primarily marketing to masses, strategy was developed on the back of consumer research. Representative samples of shoppers identified the needs, aspirations, intentions, and perceptions required to develop need/benefit marketing. The equivalent in the digital space, and perhaps even more powerful due to its customer centricity, is Voice of the Customer (VoC) data.
It is almost obvious that this powerful customer experience data should be the basis of personalization, but this data is not leveraged. The reason is that it is a sample covering a minor percentage of the digital traffic and, therefore, not vast enough to be used by rules-based or AI-based platforms that are increasingly being used to deliver messages and experiences to consumers. Most marketing technologies need data that covers a significant portion of traffic, and sample data is just not enough.
Breaking the sample barrier
VoC data is an ongoing customer-centric dataset that captures intentions, needs, next steps, satisfaction, loyalty and other metrics that are basically the most crucial and desirable building blocks of a strong marketing program.
It is not currently viable to manage specific content or experiences for anonymous individuals because we only know these things for a small sample of customers. For all of your digital visitors you have a rich behavior dataset. But this dataset is lacking the users’ intent, or their perception, or their consideration stage. Your VoC data provides that strong signal, and with machine learning, properly tuned, can observe the behavior of visitors to make an accurate prediction on the intent, the perception, or the consideration stage for each visitor to your digital property. AI capabilities can process the multitude of patterns and when fueled by structured VoC data can label visitors that have never responded to a survey.
This is how VoC data scales.
The perfect trio
You can now craft digital experiences or messaging around what stage a customer is in their decision to make a purchase i.e. researching, comparing, or ready to buy. You can know the purpose of their visit, or their purchase horizon, or key persona segments; attributes that leads naturally to content development and experience mapping.
New research can be developed, new segments tested for recognition feasibility, and new strategies implemented, all rooted in fundamental customer research. iPerceptions’ Active Recognition allows innovation in strategy as opposed to the conformity of experiences resulting from every marketer working with the same basic dataset. Leveraging stated intent data you can manage the content presented, optimize retargeting bidding or frequency strategies, or manage incentives for purchasers at risk.
Once VoC crosses the sample barrier there is a host of opportunities to build better marketing programs that deliver to consumer specifications while driving results.
VoC should be the leading dataset for marketing strategy
Voice of the Customer is a diagnostic necessity and when optimized has provided a steady stream of actionable insights that work their way through the organization until they are finally actioned.
Meanwhile, modern marketers are leveraging any data point they can find to create more relevant targeting and content for the same consumers. There is not a more relevant data asset within the organization to manage targeting and content than the VoC data.
Aligning experiences to visitor intent, needs, and perceptions will only improve the marketing results. There’s no more direct knowledge of these things than from VoC data. What has hampered the ability of VoC to take the lead is the ability to project the VoC data beyond its sample.
That ability now exists.
It is time for VoC to take the central role in Experience Marketing Automation to both improve business results and the consumer experience. If you are in VoC industry, you need to share with marketing that you have the most useful data set in the company, and through recognition technology it can be leveraged to improve the results of what they are doing.