The International Institute for Analytics predicted that by 2020, businesses leveraging data will make billions in productivity benefits over their competitors who are not using data. And this is true for the beauty industry too. The competitive advantages of data are apparent to brands focused on keeping up with rapidly changing customer expectations. And they are working on transforming customer data into actionable insights that unlock new experiences, products and services.
At the core of it, data drives enhanced customer experiences because it helps personalize the experience for each buyer. Starting from the basic customer information collected via web forms and website views and purchases, to the more granular data collected from virtual try-on sessions, enterprises can capture an enormous amount of heterogeneous data points. Analyzing this holistic customer data allows brands to study customer preferences and purchasing patterns, and use that understanding to deliver an improved and bespoke level of service. Essentially, the right products and services, recommended at the right time, to the right buyer.
Here, we bring in our experience of working with global beauty brands to highlight exactly where and how data can enhance the customer journey and experience.
Centralizing Customer Data
Before beauty brands can get to leveraging data to drive personalization, they have to first solve the challenge of data silos. For most brands today, customer data is fragmented across different systems. In-store conversations, online visits to the brand website, time spent on branded beauty applications, virtual try-ons—each of these interactions capture valuable information about a customer. But all of this gets stored in different systems, doesn't communicate with each other, and is not easily accessible across the brand’s applications ecosystem.
So the first step towards leveraging data has to be focussed on creating a cross-functional knowledge repository with a Customer Data Platform that is accessible to multiple departments. This enables an accurate and reliable data set that is consumable directly and is also flexible enough to be displayed in varied forms for further analysis and exploration.
Curating Personalized Buyer Experiences
With a holistic customer data set available for analysis, brands can start to personalize the buyer experience. This can be done across all stages of the buyer journey, right from product discovery to trials to final purchase.
#1 Personalizing Product Discovery
Beauty brands are creating simple interactive applications that gather data around personal attributes like complexion, skin type, hair type and a range of other parameters as applicable for a product being marketed. This data can then be analyzed with basic algorithms to:
- Recommend a basket of products specifically curated for a buyer's individual needs and characteristics
- Create customized formulations to deliver hyper-personalized product experiences
For most brands, committing to customized product creation might not be on the cards yet. However, personalized recommendations have become a common customer expectation. Brands that are able to successfully deliver this witness increased engagement and sales.
For the vision-care range of a global personal care brand, Srijan developed a digital advisor quiz that gathers data to recommend the right lens for a customer. It also suggests additional products to complement the buyer’s look. This solution led to a 9% increase in conversion rates.
Brands and their competitors are already on the ‘You might also like’ journey. The ability to collect and analyze the right customer data, and intelligently transform them into personalized recommendation is what takes you beyond that basic threshold.
#2 Personalized Product Trials
Beauty is a highly personal concept and so product try-ons are a critical stage of the buyer journey. As brands embrace more tech-driven solutions to enable trials, it also becomes important to plug in relevant data points about the customer into this trial process.
- Pull in data from past product purchases and suggest makeup looks combining those frequently bought products and the product that a customer is currently trying out
- Use customer data around physical attributes to a more customized set of product variants to try out
- Leverage customer interactions on brand applications and social media to identify products or looks they are interested in, and suggest those on the virtual try-on app
Because each of these recommendations is rooted in a previous customer action or information, they are more likely to engage with them. Consequently, there is also a higher probability of purchase resulting from these trials.
#3 Personalizing Product Purchase
Once the customer has chosen their desired product basket, taking them across the finish line becomes a series of intelligent nudges. Easy access to customer data around in-store, on-site, and off-site actions becomes important to deliver those nudges:
- Leverage website and application activity of customers to serve personalized ads across social channels
- Utilize customer demographic profile and purchase patterns to assess if easy payment options would prompt a buy. Deliver contextual pop-ups to showcase these options
- Scan and identify key conversations on the customer’s social media to create more personalized product offers and freebies that will prompt a purchase
Once again, because each of these nudges is based on explicit customer needs and wants, they are better placed to deliver conversions.
Create High-Engagement New Products and Services
Interestingly, the use of technology is not just limited to enhancing the customer experience around shopping. Brands, especially the industry disruptors, are starting to use data to roll out new products and services. With AI algorithms analyzing vast swathes of user data both on and off site, brands can anticipate user behavior and deliver on those even before they express their needs.
Purplle, an online beauty products and services marketplace, used customer conversations happening on their app and social media, to understand that they were looking for a chamomile-based natural skin care product. This led them to roll-out a new brand specifically catering to this need.
Interconnected revenue streams across online beauty consultation, live makeup tutorials, advocacy and advisories can be explored based on a repository of customer data:
- Use product purchase data and chatbot interactions by a customer to understand the products they use and challenges they face. Channel this understanding to create personalized online beauty routines for customers
- Monitor a customer's brand interactions on social media and identify micro-influencers who advocate brand products
This and more can be done when beauty brands start looking for data-driven opportunities at each stage of the customer journey and even beyond that. But once again, what will be crucial is having a data repository that is integrated with all customer interaction channels.
Srijan is operating in this rapidly transforming beauty landscape, and is engaged with some of the leading beauty brands to deliver digital solutions that help achieve strategic brand goals. Primarily working with AI-enriched data capabilities, Srijan is helping beauty brands create data solutions atop existing digital experiences, and deliver personalized services.
Whether it's enhancing the virtual try-on experience or creating interactive digital platforms for product trials and purchase, Srijan teams are equipped to build future-ready solutions of beauty brands.
Ready to explore how exactly your brand can leverage data solutions at key junctures in the consumer experience? Start a conversation with our expert team.
