According to an August 2013 Retail Touch Points article, 78 percent of consumers would buy from a retailer more frequently if they received personalized offers—and 71 percent don’t believe retailers are effectively providing these offers.
Although more than 50 percent of online retailers agree that personalization is fundamental to their online strategy, personalization tactics are often implemented without an established personalization strategy.
What Drives Your Business
There is no blueprint for personalization strategy. It largely depends on your business’s mix of products and customer behavior. For example, zip code demographics may be highly useful to a travel site, where certain zip codes are more likely to book business versus family travel or high ticket versus budget getaways, or have residents requiring “sun getaways” in the winter. Another site might find zip codes less useful.
The ability to mine your own data for insights primes you for “knowing thy customer.” Involve your data scientists as much as possible in your strategic planning.
The Size of Your Catalog
The larger the catalog, the more satisfying a personalized experience is. A large catalog reduces the effort required to find relevant products and content. A niche online retailer that sells a tight range of products may be able to satisfy personalization with a less complex merchandising and recommendation strategy.
The Diversity of Your Customers
Do you sell internationally? Do you cater to a mix of male and female, age groups, business and consumer, etc.? What customer personas or segments would make effective personalization targets? Which segments do you wish to prioritize?
What You Know about Your Customers
Take inventory of the data sources you can use and apply to customer segments. This may include, but is not limited to
- Account profile data
- Loyalty program data
- Demographics, zip code
- Geolocation, time zone
- Device context
- New versus returning visitor
- Referral sources such as websites, affiliates, marketing campaigns, social networks, and competitor sites
- Keyword referral data (when possible)
- Session-based clickstream data
- Site search input
- Past search, browse, and purchase history
- “Wisdom of the crowds”—people who take similar journeys tend to do X, Y, or Z, and real-time analytics
- Email program segments
- Recent site or cart abandonment
- Cart contents
- Purchase history
- Third-party and cross-channel data sources
Ultimately, as an online retailer, you want to recommend the most relevant products and offers. For each insight you can glean about a visitor, ask yourself, “how does this matter?”
One approach is to start with specific content on your site, such as the homepage banner. For example, a telecom site may serve different banners depending on whether a visitor is an existing customer or likely with a competitor.
Another approach is to work from the category or product level. How can you rank search/browse results based on what you know about the customer? Are certain styles better sellers in Florida? Has the customer previously purchased from or searched your site for a certain brand? Is the customer located in a country to which certain products can’t be shipped? Do you know a customer’s size and can you filter results accordingly? Can you serve a product page with cross-sells most likely to appeal to this customer based on his or her browsing history or past purchases?
You may also work from the persona/segment level. When a customer from segment X arrives at your site, his or her experience should be Y (on-page or throughout the site).
Your Customer Journeys
Don’t think just about what journeys are most common, but also about how you can provide a better journey. Can you use personalization to eliminate steps such as search/endless browse, maintain scent-of-intent from referring campaigns and domains, deliver targeted offers directly to the inbox, support cross-channel and cross-touchpoint activities, or encourage larger basket size? Can you identify a customer at a point of just-about-to-abandon, and prompt with live chat, offer, or other content?
Once you’ve assessed the range of the possible, prioritize your tactics based on expected impact. Then determine if there is a gap between what’s desired and what’s possible. Are you missing data sources? Are you capable of persisting data across touchpoints? Does the required data live in silos, and how difficult is it to knit the necessary data together?
Can your current technology support your strategy? What involvement do you need from IT and how soon can it be accomplished? At what cost?
Many personalization solutions don’t integrate email, mobile, in-store, plastic loyalty programs, affiliate data or even testing tools, but could greatly benefit from doing so.
For many, siloed data is only a perceived barrier to entry. The technology to pull it all together already exists today in Adobe Marketing Cloud. Adobe Marketing Cloud already has the hooks to pull in data from any system, and feed it to your personalization, testing, and analytics, with minimal involvement from IT.
The Outcome of Strategy
The point of your personalization strategy is not to do everything possible, but to ensure that all data and use cases that could better serve relevant content, products, and offers are considered, prioritized, and planned for. A documented plan also ensures that your marketers “stick to the script,” and employ the proper testing and validation processes to ensure your tactics are right for customers and your bottom line.
To learn more about Elastic Path, visit www.elasticpath.com.