The Challenges of Marketing Personalization: Not Easy, But Worth It
Personalization has been named as the top success factor for customer and prospect engagement – and with good reason. SmarterHQ points out that 72% of consumers say they only engage with personalized messaging.
Despite this, many companies are struggling to implement it – and some are failing to do any personalization at all. This article will uncover some of the struggles companies face when attempting to implement personalization, ways to overcome those challenges, segmentation strategies for getting started, and the role of AI within personalization efforts.
Personalization has never been easy
According to Phil Britt of S&P Enterprises,
“many companies lack the technology and capabilities in order to deliver personalized experiences for their customers.”
Some of the factors Britt cites that continue to work against companies looking to incorporate more personalization efforts include:
- Lack of a unified view of the customer across the organization.
- Inability to utilize dynamic content.
- Data silos within an organization – especially between the sales and marketing departments.
- Privacy concerns about data.
Even when businesses do attempt to be more personalized in their approaches, things may not go as planned. For example, Sonpreet Bhatia of MobileROI recalls personalization problems from the early days such as “a company that addressed single women about their pending nuptials or congratulated women on their first child even though they never have been
pregnant… (Pinterest and Shutterfly, respectively).”
As these examples show, when companies deal with large amounts of data and attempt to relate to their customers on a more individual basis, there is plenty of room for mistakes. However, scaling personalized marketing is possible.
How do you scale personalized marketing?
A 2019 study by Forrester Consulting found that only one in five organizations are effective at personalizing content at-scale. Personalizing content at-scale is not just a marketing effort – it requires the entire organization’s support. You must cross-reference all data, remove any data silos, and follow any privacy or legal concerns.
Scaling personalization takes intention and effort. One way to ensure that your message is going to the right people at the right time is to cross-reference all data. Britt recommends that “when dealing with subjects about which emotions run high (such as pregnancy or other life-changing events), companies should have a double-confirmation system.”
Britt also recommends using semantic and virality analysis around your customer to determine what might be most appropriate for that audience at that time.
John Choi from MobileROI discusses how important it is to remove organizational data silos in order to scale personalized marketing.
“Effective personalization strategies require organizational alignment,” Choi says.
“If sales and marketing are both sending customers content they think will be useful, rather than satisfying the customer, they’ll leave the person wondering why they’re getting two of everything and thinking they’re dealing with an organization that’s clearly disorganized.”
Choi goes onto recommend that leadership from sales and marketing teams will need to create a personalization strategy for the organization. He cautions companies to be aware of existing and pending legal regulations around data privacy.
“If customers request their data be anonymized (which they can under GDPR and CCPA), that will by default mean a certain degree of personalization will no longer be possible. Yet this is a small price to pay to build consumer trust, not to mention to avoid the severe political and legal ramifications of failure to comply.”
Mark Godley at LeadGenius recommends monitoring when someone leaves or starts a new job. He claims that this time is an important moment for the sales rep to reach out and “can send out personalized e-mails. This is scalable across thousands of accounts so that marketers get an almost real-time view into which executives are switching from customer companies to prospect companies.”
How do you balance personalization and coming across as “creepy”?
One thing some businesses struggle with is the desire to be personal in their approaches, but do not want to come across as knowing too much about a customer or being too “big brotherish.”
As Tea Liarokapi of Moosend puts it,
“the main concern of users – and by extension, your prospects and your customers (hopefully) – is not whether or not your business gathers data; they already know that you do. Rather, they feel unsure and unsafe when they don’t know the kind of data you’re gathering and how you’re using it.”
She goes on to point out the difference between younger generations and older ones.
“To the untrained eye,” Liarokapi says, “a targeted ad feels intrusive. Why? Because the recipient of the ad – in this example, my mother – doesn’t understand what cookies can do and why brands use them, so she believes she hasn’t willingly given up any information.”
To counteract that, Liarokapi recommends creating personalized campaigns using information you have obtained from your customers and potential customers by asking them or by informing them of what you’re collecting and why.
Laura Robinson of Brainlab recommends personalizing in moderation.
“Transparency and user consent really do matter. We’ve seen the trouble tech giants have been in with opaque consent flows and some outright omissions. Users want to know how their data is being used.”
How should you segment your targeted audiences?
Segmentation is a key component to building personalized campaigns at-scale. What data you should use to segment, and how to split up your audience, will be fairly custom to your business and your promotion. Robinson offers a good example of this,
“Imagine you own a business selling pet supplies nationwide, and you’re running an online flash sale on dog beds. By segmenting your audience by what type of animal they have, and then targeting only dog owners with your sale ads and your sale landing page, you’re already making small steps to providing a relevant experience to your customers.”
But couldn’t you just send the sale to everyone and assume that those who it isn’t relevant for will just delete the email or ignore the ad? While that’s true, you don’t want to get your customers used to ignoring your messaging. You do want to create a positive association with your brand – you want customers to think, “when I get an email from company X, I know it is
relevant to me.”
If you’re struggling to come up with a place to start when it comes to audience segmentation, Neil Kokemuller offers some tips. You can start with demographics or geographic information, if that is relevant to your offer or your business. He also recommends some lifestyle segmentation as well,
“In lieu of clear demographic qualities, companies often turn to shared lifestyle interests and hobbies to target customers.”
Elise Dopson adds another layer for segmentation in psychographic qualities. This includes behavior, mentality, ethics and values, and reactions to marketing activity. Dopson gives the example,
“let’s say we have an individual who resides in a large city. Their love of niche coffee and haute culture would suggest their tastes are cultivated. So, with this buyer in mind, an advertising strategy created to target them might include depictions of a bohemian urban setting, punctuated by catchy indie music.”
While it isn’t simple to obtain psychographic information, Dopson writes that when “used correctly, it can help build a strategy that’s both psychologically and emotionally resonant. And that’s important – considering that buying decisions are 20% logical and 80% emotional.”
In order to get that granular, you’re going to need a lot more than data collected in a spreadsheet. It is likely going to require turning to the power of AI.
Should you use AI? If so, where do you use it?
Many marketers are already utilizing AI in one form or another. But some of the most successful brands are using AI for personalization. Chiradeep Basumallick of Ziff Davis digs into this a bit further stating,
“AI personalization refers to the categorization of different customer data sets and extracting valuable insights from them. These insights are fed into an automation engine that can take action without human intervention. A good example of AI-powered personalization is the tailored playlists created by Spotify based on a customer’s listening habits.”
There are many ways to utilize AI personalization in your marketing efforts including AI-powered chatbots, content personalization, and audience targeting.
However, Debjani Chaudhury of Ondot Media cautions against relying too much on AI. He states,
“if personalization and automation are expected to be effective, it is crucial to find the right way to balance the two. Overdoing automation can make brand messages seem repetitive, robotic, and irrelevant. Likewise, getting too personal can overwhelm consumers. A successful relationship between consumers and brands ultimately relies on the right blend of both.”
As marketers begin launching more personalized campaigns, there are a lot of factors to consider. First and foremost, companies must decide how to get started, and implement the right data collection methods if that hasn’t yet happened. Then you must balance personalization against being too knowledgeable about your customers, as well as balance between between too personable or too automated. While it is difficult to balance all of the components, the brands who are able to do so will be the most effective.