Today, the customer journey is no longer happening merely on your e-commerce website or in your physical store. Rather, it is largely made up of instances of knowledge-sharing and conversations that are happening outside of your brand's owned channels.
And that's true of almost every stage of the customer journey—from research, to discovery, to consideration, to brand advocacy.
As social media becomes increasingly important to both ensuring a memorable customer experience and mapping the customer journey, marketers are using social listening to help formulate their strategy, gathering this type of data for three key reasons:
- Market research and consumer insights: Marketers find key conversations on social channels that should be monitored for insights, or identify conversations/new target markets to stimulate brand discovery.
- Customer engagement: Brands identify and participate in one-on-one conversations with customers and potential customers, often outside of the brands' owned channels.
- Customer experience and crisis management: Brands look for insights into customer perception across the various digital touchpoints of the customer journey, so that they might react accordingly.
The derived information provides a wealth of insights for marketers to better target those on the customer journey.
So, what social listening capabilities can you incorporate into your marketing strategy in 2017?
First, let's quickly consider what happened in 2016 and then move on to what we can expect.
Social Listening in 2016
Social listening capabilities grew by leaps and bounds in 2016, heralding new ways for marketers to better understand and target their current and potential customers. Here are a few big trends from the past year:
- Image recognition. Images were a primary media format created and shared by social media users in 2016, leading to an increased need for brands to understand the trends within images. Brands need to be able to answer questions such as "How often is my brand or product appearing in the images shared by my target audience?" and "What can I learn about my target audience from the images they share?"
- Sentiment analysis. Because of the challenges of natural-language processing, sentiment analysis itself is not an exact science; however, in 2016, more nuanced language analysis was developed, moving beyond the traditional "positive, negative, neutral" paradigm of sentiment.
- Intent insights. With the advent of intent analysis, brands have been able to better identify where people be placed within the customer journey based on their language in relation to purchase intent ("I'm looking to buy a new car") or intent to move to a competitor ("Changing my contract to another provider next week").
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