Automate Meet Consumer Expectations: 5 rules of play to automate for your customer’s needs — and serve them better


Consumer expectations are constantly changing, but recent months have particularly impacted their needs and behaviors. As brands grapple with the new challenges involved, many are wondering how to automate meet consumer expectations. The answer? Anticipate their needs. That is, be proactive rather than reactive to their needs, which is reactive.

But what does this look like in reality? Imagine you are shopping online at your favorite clothing store. Suddenly, a pop-up appears on the site asking, “Would you like us to pick your dress/pants size?” You’re surprised and delighted because it will save you time searching and filtering clothes in your size. It’s a real anticipation of your needs.

But what if the pop-up showed a different message, say, “Would you like us to pick out clothes that fit your style based on your photos stored on your cell phone?” Would you still be surprised and delighted?

While automation already allows companies to be more helpful with personalized services, being attentive to how they apply these solutions is a key element in building and maintaining customer trust.

Based on an online study commissioned by Google of 4,000 consumers in the Netherlands, Sweden, Germany and the UK, Ipsos identified five rules of the game for brands to anticipate customer needs and ultimately serve them better.

1. The “first-date rule

What do you tell about yourself on a first date? Some personalities are more sensitive than others. Ipsos research has identified what personal qualities brands should and should not use to personalize their services. These include:

  • [OK to share] General information is safe ground. This includes personal attributes that cannot be associated with a specific person, such as gender or age group.
  • [NOT OK to share]Other personal attributes, such as insurance information, medical history, race and political preferences, are absolutely prohibited. Brands that use this information when serving and communicating with customers risk seeming too intrusive and crossing the line.

2. Build a strong relationship with the customer

When a second date follows a first date and a steady relationship develops, people are more likely to share personal information with their partner. We’ve found that the same thing happens with brands: the stronger the relationship between the brand and the customer, the more customers welcome and accept brands’ use of their personal information for personalized service. Moreover, some personal attributes can only be used if there is a strong relationship with the brand, such as date of birth, spending budget, clothing size and current location.

The strength of the relationship is determined by two components: how close people are to the brand (i.e., the emotional connection) and how much people trust the brand (the cognitive connection). It is the level of proximity to the brand, in particular, that affects brands’ use of more personal information. The closer people relate to a brand, the more personal information brands can use.

Automate Meet Consumer ExpectationsAutomate Meet Consumer ExpectationsAutomate Meet Consumer Expectations

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3. Help customers when they’re short on time

Customers like personalized service more when they are in very difficult situations and have limited time or energy to complete a task. This could be, for example, because they are rushing to catch a train, working under a tight deadline, or late for a meeting with a friend.

In these situations, clients benefit most from services that help them save time and energy. In situations where customers are calm, relaxed, and have plenty of time, personalized services delivered by machine learning will be less welcome and helpful.

4. Help customers when they need it most

Customers like personalized services more when they are in public places (public transportation, at work, at the store) than in private places (at home). Public places elicit a higher need for quick and accurate help, while in private places customers need less help and are likely to be more patient.

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5. Take into account the industry you work in and the consumers you interact with

Research has shown that customers are especially happy to get help when it comes to banking and savings, but are less receptive to personalized service when booking a trip or buying clothes. This is likely due to the fact that they feel less confident about financial tasks.

The data show that the customers most likely to accept a personalized service are women ages 18-34 with young children. In contrast, older men (50+) are least likely to accept a personalized service. This means brands can be bolder about offering personalized service to the former, but should be more cautious if their audience falls into the latter category.

Applying these five rules of the game will help brands better serve their customers, building trust and being able to surprise and delight them by anticipating their needs.

Dive deeper into the topic

When are automated services accepted? And what personal information are brands allowed to use? Download the full research report to begin building brand engagement with automated services.

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