How Voice UI brings new meaningful analytics to QSR in web, mobile & telephony
The metrics QSRs expect are akin to any e-commerce experience in a tap-and-click graphic interface. The systems may vary in name, but the intent and, thereby, data points tend to be the same:
- Online Surveys
- POS/CRM Data
- Web/App metrics
- Online reviews
- Delivery sales data
This data is typically informed by a web or mobile interface limited to tap/swipe or point/click/type interfaces. There are two widely used direct customer feedback tools, and both require notable effort to obtain:
- Customer Interviews
- Customer to Staff feedback
The ability to capture direct, natural language feedback in the moment of engagement has been impossible until now.
Exposing a voice user interface to the QSR digital experience, informed by an NLP model, is a new level of customer interaction, feedback and insights gathering. Allowing the customer to speak to your web or mobile ordering experience brings an in-store ordering experience to the customer’s device and, with it, the exact language customers use with your brand.
The NLP model ensures that the variety of customer language used maps back to the brand’s own nomenclature and offerings and informs the machine learning or AI.
All this informs a new suite of metrics that can inform not only general usage but new information as well:
- The ordering process (how do people think about their order with your offering)
- Customer Language (how are people speaking about your offering)
- Customer Desire (it’s hard to ask for something that isn’t available in a Graphic UI, but with voice, you understand what customers want)
- The sentiment (where are customers getting frustrated or delighted)
What can you do with all this new data and information? Let’s unpack it.
By knowing the ways in which customers are ordering verbally, you can inform the presentation of your offerings visually across your digital systems. This data can also inform marketing and advertising initiatives by speaking to your customer base in how they verbally process information.
The language your customers use is an invaluable resource. By understanding the words, their order, and how they connect to your NLP model, you gain insights into how the customer thinks and communicates. This information can inform menu design, product branding, development, and marketing initiatives.
One of the myths of voice and conversational AI is that it needs to solve everything. That isn’t the case. What the industry categorizes as ‘misses’ or ‘failures’ are often desired, like website bounce rate; a healthy ratio of success to failure means the experience is working and evolving. This data can form branding, product design, and copyright and trademark strategies by informing the business of customer language without waiting for expensive and time-consuming customer feedback cycles.
It is nearly impossible to understand how customers feel when they point, click, tap, and swipe through your digital interfaces or speak to an existing IVR system. With a voice UI and conversational AI platform, you can listen for language and tone used to anticipate when frustration is escalating or when delight is happening. This data empowers brands to make powerfully informed decisions around the customer experience. Not only within the voice user interface but across the organization.
Bringing a voice user interface to your existing customer touchpoints isn’t as challenging or time-consuming as you think. In fact, there are many strategies to stair-step the capability into a variety of endpoints all at once in a limited capacity or by focusing on one, testing and learning, and then cascading it across others. It depends on the business and its needs and tolerance for the duration of the deployment. And Voicify QSR customers are seeing first iterations roll out in weeks, not months.
Want to learn how? Just ask us!
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