How To Augment Customer Experience With Omnichannel Personalization

Omnichannel personalized marketing is no longer just “nice to have” in today’s marketplace, especially with customer experience becoming a key brand differentiator.

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Consumers are now interacting with brands across multiple channels. Not only do they expect relevant content but they also want the ability to “pick up where they left off” when they switch from one channel to another.

Many retailers consider implementing omnichannel personalization as one of the key strategies to generate growth and increase revenue through providing a customer-centric brand experience. In fact, many retailers see an increase in revenue and new customer conversion rate when they start offering personalized customer experience.

A study by Invesp has shown that personalization has been proven to improve customer loyalty and increase conversion:

  • 53% of online shoppers consider customization valuable.
  • 45% of shoppers prefer to shop on sites offering personalized recommendations.
  • Personalized ads have a conversion rate 10 times higher than “one-size-fits-all” ads.

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However, there are many moving pieces to ensure the successful implementation of such strategy, including the collection, integration, and synthesis of a large amount of customer data and the ability to turn it into actionable insights.

Thankfully, there are many tools you can use to help gather customer data and apply them to improve customer experience. Here are a few helpful features to look for:

Customer Data Management (CDM)

Information on your customers’ behaviors and preferences will help you cultivate relationships and increase retention rate. Data collection is the first step to implementing a personalization strategy.

To see CDM in action, look no further than online retail giant Amazon.com. Customer information is collected and utilized for making recommendations that leads to increase in sales, as well as improving customer relationships with more personal services.

To get the most out of your customer data, you should:

  • Decide on the critical data to collect so you don’t end up having to parse through irrelevant information
  • Clean up your data to avoid duplication
  • Funnel all information into one centralized database to construct 360° customer profiles
  • Avoid siloed internal practice and encourage collaboration between departments
  • Make the information and customer profiles easily accessible to sales personnel in the field.

Customer Relationship Management (CRM)

After you have constructed 360° Customer Profiles that aggregate your customers’ unique preferences, brand interactions, and habits, it’s time to take that information to the next level.

You can leverage the analytics capabilities of your software to make data-backed business decisions based on the level of brand interaction and projected lifetime value of each of your individual customers.

To leverage the power of CRM, follow these best practices:

  • Create targeted content for specific customer segment to help your brand stay relevant and top of mind. For example, P&G developed the Being Girl microsite to share relevant content with a specific customer segment
  • Use geo-location to target customers who are in the vicinity of a physical store
  • Learn customer habits and preferences to create offers and deliver services that are timely, customized, and relevant
  • Implement Omnichannel marketing and customer care to deliver a seamless customer experience across all touch points

Automated Personalization

You can also leverage the information about your customers to create personalized campaigns and communications that help you deliver the most relevant information to specific customer segments in a timely manner.

This will not only allow you to nurture customer relationships and improve retention rate but also entice new customers to engage with your business by sending out highly relevant offers at the critical moments of their customer journey.

These are some of the ways you can leverage automated personalization to increase sales:

  • Segment and target high-quality leads that are likely to convert
  • Implement personalized lead nurturing campaigns to deliver the most relevant content and offers
  • Increase customer lifetime value by improving customer satisfaction and loyalty with relevant offers
  • Leverage your social media presence to deliver a seamless experience that moves customer along their purchasing path

The Best Marketing Speaks To What Makes Your Customers Tick

The effectiveness of one-size-fits-all marketing messages is plummeting as consumers are becoming increasingly savvy and expect for customized content and offers from brands.

As a marketer, you need to deliver a personalized customer experience across all channels and make sure your copy, content, and offer are highly relevant while appearing in front of your audience in the right place at the right time to get the highest ROI on your marketing budget.

Stop Dirty Data: 5 Steps to Data Cleaning

One of the biggest issues we see our clients have is dirty data; that is, inaccurate, erroneous, or otherwise incomplete data. While this may seem like a tiny blip in the realm of big data and analytics, it is quite possibly the biggest barrier in enhancing a company’s overall data insight capabilities. Here are 5 steps to data cleaning and ensuring data integrity.

1.) Know Your Data

Before you even attempt to start cleaning up your data, you need to ask yourself: What is the data used for currently and how it will be used in the future? Without a direction of how the data will be used, it will be difficult to clean it up because you won’t know what fields to eliminate (if any) or understand what glaring gaps lie within the data. We were given a task from by a client to clean up their data and bring it all in one place. When we presented the pristine, cleaned up, data it to them, we asked them what it would be used for and their response was they had no idea!

Bottom line: if you don’t know what your data will be used for, you will have a much harder time knowing where to even start the clean-up process.

2.) Sanitize Your Inputs

Let’s talk about how your data ends up in a database. Jane registers for a website and enters her name, e-mail address, and zip code. Her e-mail address is stored within the database with an extra space due to the input of the form, so instead of “janedoe@mail.com”, it reads as “janedoe@mail.com “. While this may seem insignificant, having that extra space will make the email field unreliable and could cause problems with how the data is read in other programs. Cleaning up your currently stored data is all well and good, but if you haven’t purified your inputs, there will be a continuous loop of bad data.

3.) Identify a Unique Field

This may seem like a no brainer, but without a unique field, harvesting your dataset will be much more difficult. Databases such as SQL and MongoDB insist on storing a unique field, labeled Primary Key or Object ID respectively. This unique field is important in identifying links between two tables, so you are able to append data from one table source to another.

For example, let’s say you have two separate tables: your customer list and your e-mail campaign data. Each customer has a reference number which is located in both tables. In order to link the customer data to the e-mail campaign data, having the unique reference number is vital in connecting the two tables.

4.) Validate Your Fields

If you pay attention to only one step in this article, this should be it. Validating your fields is vital in cleaning up your data.

Remove Spaces

Having spaces in your data could directly affect the readability if another software or API needs to read the information. Be proactive in removing any unnecessary spaces in your fields. If there is truly a space in the cell, the =TRIM function in Excel eliminates the unnecessary spaces.

Remove Illegal Characters

Sometimes illegal characters make their way into your otherwise clean data. We all know naming file names on your computer with characters such as #$%^& will elicit an error response, and the same goes with cell data. For example, let’s say you have a “date” column, and for whatever reason the “#” symbol is being inserted in every row. The date column will not read as a date column but as a text or general column.

Do Not Store the Date Field as a Text String

The date column is crucial in determining when an event took place. Let’s say you want to view the revenue for the past year that were attributed to your e-mail campaigns. If the e-mail sent date field is reading as text and not an actual date, you won’t be able to filter the data to gather your revenue.

Store E-mail Address as Lowercase

For consistency purposes, it’s important to store your customers’ e-mail addresses as lowercase. If you store a customer’s e-mail address as uppercase and he/she then decides she wants to unsubscribe from communications, the e-mail address may not get unsubscribed because of case mismatch.

5.) Keep Tomorrow in Mind

Looking ahead when it comes to data organization and cleaning will save you valuable chunks of time in the future. Not all data fields may be useful immediately, so hiding and safekeeping seemingly useless information instead of deleting fields will help save time and money when business needs change. Process guidelines for data structure guidelines may be time consuming to make, but it will mean a world of difference when explaining data entry and manipulation to new hires and other team members.

Consistency is the key to a cleaner data future.