Next Best Offer: Predicting Your Customer’s Wants Before They Do
Updated: Feb 7
Try to sell the same kind of soap to different people and you will fail miserably.
Today’s market doesn’t work on the mass sell approach. The consumers are anyway frustrated with the generic offers they see on every platform. These lazy marketing techniques not only require a lot of investment but are low on impact and impression creation. Companies today are focusing more and more on interactions that are personalized and relevant, based on a consumer’s needs and preferences.
Predict Your Customer’s Wants
Presently, very few marketers are able to make relevant offers to their customers. For examples, despite not owning a credit card, almost all the customers receive more than 300 credit offers, which not only frustrates them but also leaves a terrible impression of the brand in their minds. The typical consumer here feels bombarded with messages, that he considers irrelevant.
Since many companies treat all their consumers like a generic audience, failing to provide tailor-made communication, they lose out on many great opportunities. This can lead to them invariably losing ground to their competitors and rivals.
Next best offers, the next best solution
Historically, retail sales meant a personal bond with the consumers. Salespeople knew each other as well as the customers they were catering to. But that era is long gone. Today’s retail stores lack the personal touch and the only way to build a loyal customer base is through technology and data analytics. In particular, the next best offer is a way of providing better and more precise marketing.
A next best offer (NBO) is a highly customized offer by a company or marketer, that guides the customer to the right merchandise, services, or information, at the right moment in time, at the most agreeable and attractive price, via the most convenient channel.
Mostly NBOs are made to inspire a purchase, drive loyalty or both. An NBO can be the focus, product or service driven. A next best offer may be delivered through one or multiple channels.
It is typically derived from data mining, segmentation, statistical analysis, and predictive modeling, and then executed based on business rules.
But why should companies care about NBOs?
If they don’t, they will see their customers deflecting to competitors that do.
Customers are bombarded by offers day and night, they will only pay attention to the ones relevant to them.
New technology, such as SoMoLo (social, mobile, and locational), can be leveraged to create greater relevance.
Bad NBO executions can have a harmful effect and can drive customers away.
How to create an NBO
There are four simple steps to it-
1. Defining objectives and strategy
There is no point of a strategy without an objective in mind. The objective can be something like an increase in revenue or achieving a greater share in of wallet. For example, retailer Tesco established NBO objectives of increasing sales to regular customers and enhancing loyalty.
2. Gathering data
This involves figuring out what sources of data can be used to target customers through offers etc. This can include internal data or external data, for eg. SoMoLo data. The most important types of data have demographic and psychographic information, data about companies product offerings and about purchase context including channels, reasons for purchase, customer emotion and time of the day. Walmart is capturing and leveraging SoMoLo data to drive online purchases and is using location-based technologies to guide customers in their stores.
3. Analyzing the data and executing an NBO
This means turning data into actionable insights through advanced analytics processes which include data segmentation, data modeling, using business rules, delivering offers through various channels and engaging widespread experimentation.
Companies such as Starbucks, Qdoba Mexican Grill, and Nordstrom provide examples of organizations that are using different methods and channels to test various offers.
4. Learning and evolving
Pursuing NBOs means engaging in a constant process of learning and evolution to predict your customer’s wants. CVS is a company that is constantly learning and evolving by delivering different types of NBOs to different customer segments in different ways. CVS illustrates an organization that has made NBOs and the process of experimentation part of its culture.
To build your own NBO, visit us at Datahut, your big data experts.