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By layering machine learning on top of your existing customer experience solutions, companies can up the ante on their personalization efforts PHOTO: chuttersnap

People have grown accustomed to companies offering them personalized experiences — so much so that they have begun to expect it as the norm. Indeed, in a recent report titled “The AI Revolution,” Salesforce Research reports that 51 percent of consumers and 75 percent of business buyers expect companies will be able to anticipate their needs and make relevant suggestions that by 2020. 

Many companies already offer personalized online experiences in varying degrees, depending on their industry, and we often don’t even realize when it’s happening. Only when the experience falls short do we notice it, by which point we’re frustrated. The next time you’re on a website and see a map showing you locations nearby, take a moment to recognize that the experience has been personalized to your specific search.

Because it has become standard, personalization has upped the ante on meeting customer needs. As people get used to personalized experiences in every interaction, we as customer success leaders must rise to the occasion. But what does this mean for the customer experience? By the time customers reach out to you, they most likely already have problems, are unable to find solutions and are expecting you to provide the information they need, quickly. 

Tailoring that information to individuals begins with understanding what information is most likely to solve a particular query, and delivering that information as intuitively as possible. In this endeavor, data and technology will be your best friend. By layering machine learning on top of your current customer experience systems, your customer service operations can remain agile, scale with ease and become more relevant to your customers.

5 Ways You May Be Dropping the Ball on Personalization

Here are five ways you might be behind the curve when it comes to creating a personalized experience for your customers.

1. Relying on Outdated Modes of Gathering Information

Customer surveys are important, but they shouldn’t be the only way you are collecting information to understand people’s preferences. The responses you get could be biased or written without fully understanding the questions. By overlaying machine learning algorithms on top of your customer service solutions, you will be able to draw inferences on customer preferences directly from their habits. 

Furthermore, machine learning will enable you to segment your audiences and track unbiased metrics on content consumption to determine what they are finding engaging and useful. Models can be applied to the data that might help you discover patterns or draw conclusions that we humans can’t see because of our inherent biases.

2. Not Using the Customer's Preferred Method of Communication

Pouring money into an agent-assisted service strategy when your customers prefer to find answers to questions autonomously online will waste your company resources and cause relationships to deteriorate. If you collect information about how your customers engage with you across channels, the data will reveal your most popular channels and help you decide where to invest. If you find that the majority of your sessions are happening within your customer self-service community instead of on your website’s FAQ page, you have uncovered important information. 

Once you understand which channels your customers find the most valuable, you can then take action to dig deeper into why and invest more into the platforms that need it in order to provide a vibrant omnichannel experience.

3. Providing a Messy Self-Service Environment

Forrester Research has reported that 72 percent of U.S. online consumers prefer to use the internet to get answers to their questions, rather than contacting a company via telephone or email. The shift in preference to self-service means that we must offer the best self-service experience possible. Scan all of the areas your customers could currently turn to in order to answer their own questions and evaluate the performance of each channel. Self-service portals, your company blog and FAQ pages are all excellent places to start. Record customer interactions on these sites with tools like Hotjar, so you can evaluate the user experience you’ve created. 

Making information easily accessible is the first step, but that step alone will not yield any results if you don’t provide the right information. Track click-through rates and click rank rates on the content you’ve suggested to customers to see if they are actually reading and finding it useful. With audience segmentation, you can break this down further to group customers by common traits to see if there are patterns in what they find useful as a group. This is the start of personalization.

4. Failing to Equip Support Agents With the Right Information

Just as it is crucial to get your customers the right information, your support agents also need to be equipped to find the best information in a moment’s notice. Provide your support agents with tools that will help them quickly solve common customer concerns so they can spend more time on complex issues and avoid escalation. 

One example of how this can greatly benefit your organization comes from Medallia. Medallia made it easier to get content that helped solve common problems into the hands of their agents, which led to Tier 1 agents handling 34 percent more cases on their own without escalating to Tier 2. As a result, the entire customer experience improved, with Medallia experiencing an amazing five-point improvement in its net promoter score (NPS) in one quarter.

5. Waiting for Customers to Tell You Information

Being able to intuitively offer personalized and relevant information to your customers before they begin to submit a query is quite possibly the most impressive thing technology can help us do. Think about your own experiences with online shopping, for example. Thanks to Amazon, when you’re looking at products online, it’s no longer a surprise if a website is able to recognize patterns in what you search for and takes steps to recommend similar items. Ecommerce is not the only online experience where we can now deliver that relevance. Using data, anticipate what your customers are going to want next, and then find ways to deliver.

No Need for an IT Overhaul

Technology is enabling us to understand customer preferences in ways that would have been unimaginable 20 years ago. One of the biggest myths surrounding implementation is that your business needs a complete overhaul to start benefiting from these new technologies. A digital transformation doesn’t have to be that disruptive; you just need to be willing to explore innovative technologies and incorporate ideas that will enhance your current offerings. That will set you apart from the rest from the pack.