Challenge # 1 

Failure to turn data into a useful tool 

The boundaries of the online and offline worlds are becoming less clear, more and more data becomes available for analytics. It would seem that this flow of information creates opportunities for additional segmentation of the audience, to increase its loyalty. But here lies the complexity - you need to be able to collect data from all sources, store and keep it up-to-date in such a way as to interpret it qualitatively and build logical chains. 

Solution 

To organize a large amount of disparate data, companies create a centralized storage space. This could be a CDP (Customer Data Platforms designed to aggregate consumer information from various sources and marketing automation), a cloud-based database, or other solutions. Such a “storage” will help create a single customer profile that is updated at the time of performing actions, which is critical for creating loyalty programs. 

According to a survey by the international marketing agency Merkle, 53% of companies are at the stage of searching for a solution for organizing and storing data. The main challenge lies in finding the optimal technological solution, one that is most suitable in terms of functionality and at the same time its implementation will be cost-effective. 

Some companies settle on the CDP option, others are less decisive because they have already experienced the technological hype and overestimated new technologies. For example, many have become frustrated with cookie-based data management platforms (DMPs) as third-party cookies become an unreliable source of tracking. 

The truth is that there are many different CDP solutions on the market, so it is important to clearly define the company's goals, system use cases, key performance indicators to justify costs, and the rate of return on investment. Speaking of payback, 37% of companies took nine months to do this, while the other 30% took only six. 

Challenge # 2 

Poorly prioritized customer service 

Many companies get too carried away with attracting new audiences and forget about maintaining interest from existing clients. On average, it costs five times more to attract a new client than to retain an existing one. The golden rule of any business is to build loyal relationships with clients, thereby avoiding the cost of finding new ones. However, about 44% of companies pay more attention to attracting customers, and only 18% of companies are focused on retention, according to the American marketing agency Invesp. 

Solution 

In a highly competitive market, only client-oriented companies survive. This concept implies not only meeting new clients bonuses, but also rewarding old clients for their loyalty. Invesp published an interesting statistic: the probability of selling to an existing client is 60-70%, while to a new one it is only 5-10%. In addition, loyal customers spend 31% more than new ones. 

Quick adoption to changing circumstances, constant update of offers and an individual approach is the main way to increase the audience of regular customers with the help of a loyalty program. Data collection should not take place for the sake of accumulating information, it is important to process it correctly. 

Using regular surveys, loyalty tools such as discounts, bonuses cashback.  

Challenge # 3 

Interpreting Data Right

Competent work with data allows to build patterns that directly affect the company's policy. For example, when deciding whether or not to grant a loan or an installment loan to a client, banks are turning to score, which increasingly includes checking the “digital footprint” on social networks. For example, being in online network marketing groups increases the risk of non-payment of debt, and being active in communities about travel and finance lowers it. 

When using information this way, you need to be sure that it is interpreted correctly. It happens that not always coherent actions of customers are combined and conclusions are drawn that do not correspond to the real needs of users.   

Solution 

It is important to remember to look for more voluminous data, mixing internal information about the behavior and transactions of customers with external information. 

Retail stores can enrich information collected from reward cards, mobile apps, websites, direct customer interactions, and by purchasing information from third party companies known as data brokers. They collect data on their own and acquire it from other organizations commercial companies: banks, dating sites and government agencies, for example, census data or vehicle registration data. Data brokers create "profiles" of people with information about habits and behavior patterns. Retailers then match their loyalty card data to these profiles, creating a clearer picture of shoppers. 

Summary