As discretionary spend decreases in inverse proportion to cost of living increases, and consumers think more carefully about where they spend, retailers have to get really smart about strategies to win and retain their share of the market. There’s one approach that is proven to work to engage customers, enhance their experience and increase spend – and that’s personalization.
iVend helps retailers to capture and analyse customer data.
Read how our analytics system helps retailers with personalization.
Retailers who understand their customers and use that knowledge to personalize customer engagement benefit on two fronts:
Closing the gap – between the online and instore experience, to offer a true omnichannel retail experience. Online shopping is intrinsically more personalized – a customer can be greeted by name, shown previous orders, receive suggestions for items they might like and have their payment details stored for seamless checkout. In the store it’s harder to achieve this, but with smart personalization strategies, you can close the gap between online and offline.
Widening the gap – between you and your competitors. We know that customers demand personalization, so the more you can offer it, the faster you can stride ahead. Research shows that a massive 80% of consumers * buy more from a store that personalizes their shopping experience, and that personalization can increase revenue by 5 to 15%. ** In fact, today’s customers take personalization as read – with 66% of shoppers *** expecting retailers to understand their personal needs and expectations – which is why personalization also helps to reduce the cost of winning new customers by as much as 50%. **
Steps to personalization
If you want to offer (more) personalization to customers, there are several key steps to follow:
- Collect data about your customers
- Extract insights – use analytics to mine the data to understand customer preferences, demographics and buying behaviours.
Use those insights to build personalized offers, identify your most loyal and profitable customer groups, re-engage with shoppers who haven’t purchased recently and segment your audience to send differently targeted promotions.
The importance of retail data analytics
As you can see, analytics for retail is at the very heart of personalization and therefore successful growth. Research from Forbes shows that retailers who use analytics have a significant competitive advantage. + There are four types of analytics, each of which plays a role in helping to deliver effective personalization:
Descriptive – this tells you what is going on in the business. In terms of personalization, it answers important operational questions about the response to a personalized promotion, such as what was the conversion rate, who engaged, did sales increase, how did the audience engage – what was the mix of online, mobile and social media?
Diagnostic – this identifies areas that need attention. For personalization, this could tell you which of your activities and personalizations are not generating the required results, or whether certain groups of customers are not engaging/engaging less frequently. It will give you the detailed data to drill down into the reasons why campaigns are not working.
Predictive – this looks at trends and what the future might look like. You can use this understand shifts in customer behaviour – by demographic groups, store, region, product category or time of day. This data helps you to pre-empt demand and plan personalization activities to meet it.
Prescriptive – this type of analytics suggests next steps. It might, for example, show you that based on the success of a personalized promotion you ran for customer group A, the next step should be to tailor it for customer groups B, C and D.
Three things to look for in your retail analytics system
- Can it capture data from a wide range of sources?
The best analytics results come when the data is drawn from the widest range of systems – this could include retail POS analytics, mobile POS, online store, loyalty, sales, marketing and social media, promotions, inventory and finance.
- Is analytics part of an integrated digital retail technology platform?
By far the best way to do this is to ensure that your retail analytics system is part of an integrated digital retail technology platform. This means that all your retail systems operate within a single platform and can share data. With an integrated digital retail platform, there are no data silos, makes it easier to capture and analyse information from all around the business.
- Does your retail store analytics provide both high level and detailed information?
A good retail analytics system provides at-a-glance dashboard-style information for immediate decision making, but also the ability to drill down into more detailed information for deeper analysis.
As times get tougher for shoppers, it becomes even more important for retailers to meet their needs through personalization, and the key to success is the power of data and analytics.
What does personalization look like to the shopper
Personalization can take many forms, including:
- Curated suggestions for products they might like to buy (based on their previous purchases).
- Promotions and offers on items they actually want – where the offer might be a discount; a multibuy (buy one get one free/buy one get one half price)
- A ‘refer a friend’ offer where both get a reward – perfect for finding more people like your best customers
- Personalized invitations to events – such fashion shows, cookery demonstrations, make up demonstrations, DIY events or co-branded events with key suppliers
- Offers based on special events such as birthdays, wedding anniversaries or holidays.
What other technologies play a part in personalization?
Your loyalty program is a rich source of customer preference data, telling you who buys what, where and when. It also helps to deliver personalization in store, at the checkout or via a mobile app. Your online store holds a wealth of information about customer purchases and preferences. In store mobile POS can be used to capture customer data in the store, and also to use personalization to enhance the customer experience.