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Why & When to use Bots?

Bots have been garnering a lot of attention recently. The majority of coverage has been positive but it has also garnered negative attention as it relates to Russian bots and their involvement with the 2016 election. Regardless of sentiment, bots are simply a software application that can perform tasks and computations much faster than a human. Bots have been around for quite some time and there are thousands of Bot applications in use today. Many of which provide useful services for consumers and help drive positive customer experiences for brands every day. Brands use Bots for a variety of reasons, some of those include but are not limited to:

  • Engaging An Audience
  • Collecting Feedback and User Insights
  • Facilitating the Sale of Goods and Services
  • Integrating Customer Service Across Digital Touchpoints
  • Personalizing Experiences

Similar to the explosion of websites in the 90’s, brands are spinning up bots because it’s a hot digital marketing buzzword and everyone seems to have one. However, Bots only make sense when it fits strategically with your Marketing and IT roadmap and more importantly, aligns with your brand promise. The two examples below, Dominos and Poncho, use a mix of natural language understanding (NLU), machine learning and artificial intelligence to drive the conversation with their users. These two Bots are not only highly functional and intuitive, they each support their brand essence and key business drivers. The Dominos Bot allows users to engage on their channel of preference and makes ordering pizza quick and seamless. The Poncho Bot supports the vision of the company which is “to build the chattiest, friendliest bot that would actually become part of your daily routine”.

On the flip side, there’s Zappos, which is a customer service company that happens to make shoes. Zappos, a leader in the customer service and experience space, currently does not employ Bots as part of their customer engagement mix because they feel it does not fully support their goal of creating personal and emotional connections. Zappos, as seen in the screenshot below, prefers customers engage first on voice and then chat and email as secondary channels.

Zappos bot

Leveraging Bots to Improve Mystery Shopping

As the above examples show there are many different ways to use Bots or some companies choose not to use them at all. However, at MaritzCX we believe there may be ways to use Bots as part of a Mystery Shopping process. By doing this you can directly impact the shopper experience and ultimately improve the quality of the deliverables for your clients.

Integrity of Shopper Data

At the end of the day, the reports and analytics generated are only as good as the data feeding them. The information gleaned, and recommendations produced are suspect at best and un-usable at worst if the integrity of the data is compromised in any way.

Delivering quality data and insights to our clients is highly dependent on the frontline worker—to our shoppers. In an era where customer expectations continue to rise as the Amazon and Ubers of the world set the bar, how can organizations continue to optimize processes, mitigate project risks including bad data, and ultimately improve solutions and deliverables to clients? There are many ways this can be done, barring normal project constraints (time/cost/quality). For example, you could integrate wearables into the shopper experience, leverage augmented reality, or use drones to take videos of sites. While these options may seem far-fetched and unreasonable, the need to continually push ideas and concepts is one way to be viewed as a trusted advisor.

User (Shopper) Experience & Customer (Client) Experience

  1. Knowledge Base– Today, when shoppers have an issue or a question, they either comb through hundred-page guidelines, call their project supervisor, or a combination of the two. For each project, imagine if the project guidelines and scripts, client brand standards, operating procedures, and common know-how elements were digitally stored and accessible via a Knowledge Base (KB). Shoppers could simply SMS their query and immediately get a response and/or set of likely answers for quick resolution. They would not have to page through a document, hope someone answers their phone call, and they could do this during non-peak business hours or when it’s convenient for them. Having shoppers armed with a customer-support vehicle will enforce governance and provide immediate and clear direction for shoppers if and when there’s any ambiguity.
  1. Notifications– Ensuring shoppers get to their destination is a top concern when running a mystery shop program. We cannot prevent obstacles that sometimes are bound to happen such as weather systems, family emergencies, illness, etc. However, a common issue is shoppers going to the wrong location. This should never happen with today’s technology and mobile enabled workforce. There are many uses for notifications, but in this case, shopper records could have all their job sites loaded in a database (dB) and synced with Google or Apple maps. Push notifications can send an alert along with driving directions and anticipated route times to their device.
  1. Data Input– Today’s version of natural language processing promotes richer responses via keyword spotting. Taking this a step further you can augment this with a rules engine that provides grammar auditing, recommended or suggested inputs, and checks against other reviews and/or historical data of a particular site. This will help maintain the consistency of shopper feedback and provide common vernacular used across the shoppers.

Our job as trusted advisors, is multifaceted and delivering exceptional service and insights based on sound data is expected from clients. Yes, executing on a program is critical and should not ever be overlooked, but providing strategic consulting is equally important and provides a competitive advantage when customers are deciding who to partner with for their Mystery Shop program(s). Using bots to assist mystery shoppers mitigates risk of common mystery shop issues, helps ensure the data collected is consistent with program and brand expectations, and gives shoppers a tool to more efficiently and accurately record data.