How B2C Companies are Finding Sales Success

Using Big Data

In the B2C sector, Big Data is a hit because of its real-time functionality. The success of this list of companies is a testimony to the value of Big Data

Amazon is able to generate over 25% of its sales using its popular recommendations engine that suggests products of related interests to consumers.

Tesco uses its loyalty program to collect purchase data, which they then use to make a variety of decisions, including the micro segmentation of its customers to optimize product mix, pricing and promotions.

Vera Bradley switched from sending shoppers blanket email promotions to sending targeted offers based on individual shopper purchases. As a result, Vera Bradley sent 63% fewer emails but generated a 101% increase in shopper clicks.

If you haven’t started using big data yet, it is high time you did. In the B2C industry, Big Data has proven to be extremely valuable for recognizing trends and reaching out to buyers and prospects with laser focused selling strategies.

To make the best of all the available data floating around, you have to be able to use and structure the data. Here are a few tips how to do that

How can you make Big Data work for you?

Identify customers with most value: The first step toward a  good sale is identifying the buyer who is most ready to buy. With many people visiting your site or frequenting your brick and mortar stores, you need to know which of them are of the most value to you. Use advanced analytics to spot your buyer in real time. Calculate their level of interest and meet their expectations though your understanding of in-depth prospect data.

Micro segmentation: Segmenting target groups has been around for ages. The difference today is that you can break them up into smaller, more defined segments. Using Big Data, you can fine tune your segmentation and cater to them through highly personalized campaigns.

Determine optimal selling techniques: Big Data lets you identify your prospects’ interests. This data on consumer behavior helps you to strike a chord with prospects in your responses to their activity. Determine your selling techniques and then easily refine them on-the-go to be able to connect with prospects at every stage of the buying cycle.

Identify cross-selling or up selling opportunities: Big Data driven insights are highly effective in forecasting buying behavior. E-commerce giant Amazon has been using this technique for years. Tracking variables like past behavior, often-visited products or sites, and individual buying trends can allow you to effectively cross sell or up sell.

Dynamic pricing: Pricing is an important element for a prospect’s great shopping experience. Imagine yourself hunting for a specific pair of expensive, high-end trek shoes. You check out various sites, maybe even drop by some local stores to compare prices. Soon after, you find a discount coupon waiting for you in your mailbox. You think you can resist that?  Real-time loyalty

coupons, promotional offers and smart pricing are elements that make for a great shopping experience. Use your data to enhance your buyer’s shopping experience.

Analyzing lead behavior: Today’s buyers spend a lot of time on product research before making a decision. The journey from the awareness to the buying stage is crucial and this is where you need to understand your leads better. If you were to offer relevant products with a strong, reader-focused selling copy, your leads will be more interested in you. So Big Data gives you an insight of not only what leads want, but also how you can interact with them.

Conclusion

A stat by Baseline mag states that a 10% increase in data accessibility translates into an additional $65.7 mil in net income for a typical Fortune 1000 company.

Using Big Data, you can create a highly personalized experience for your shoppers irrespective of which stage of the buying cycle they’re in. Making Big Data an integral part of your sales strategy can win you more leads, close more sales and convert buyers into loyal customers.