Segmenting the market, customers, leads is an exercise we do every day. The goal is always the same: to identify a point of attention in people, an extra lever to propose content as close as possible to their needs. Today companies can collect a lot of information on users, in a very complicated scenario. This information has the characteristics of big data: there is a lot of it, it changes quickly, it is of different types. For this reason, before implementing a marketing automation project , it is good to integrate the data as best as possible for the construction of refined segments.
To build segments for marketing automation, you need to approach data with a certain method. Here are the steps to get started on the right foot:
Mapping
The first question to ask is: which data, in which platforms? A marketing automation project cannot ignore a preliminary analysis of the management of a company's information assets. It is therefore essential to verify on which platforms all the potentially available data reside: CRM, e-commerce, loyalty cards, ERP, cash register systems, etc. Subsequently, it is necessary to understand which of these are functional to business objectives and focus on what is truly useful, distinguishing it from what is "noise". You probably have a lot of information, but it is not a given that all of it contributes to the creation of segments. Some may be irrelevant from the point of view of journey analysis.
Normalization
Marketing automation platforms typically manage different data sources and also take care of their normalization: they verify the data quality and acquire it only list of antigua and barbuda consumer email if correct. In some cases they intervene by correcting the fields following pre-established rules (for example, they introduce the country code in the telephone number field). In others, they return lists of errors that can be verified. Finally, the technology automates data matching by linking the information to a single user and discarding/reporting duplicates.
Synchronization
Data synchronization is an aspect that typically must be customizable based on the company's needs and timing is often linked to the business model. Real-time synchronization can be expensive on high volumes, but in many cases it is necessary to give users an experience that is always updated on their preferences and engaging on the communication level. It certainly cannot be a manual activity but, if it cannot happen in real time, it must be scheduled based on the strategy.
Creating a segment from data
As we said in this post, segments can be of two types. We consider static data to be those based on information with a low level of updating, which can certainly change, but with a reduced level of speed and not with a high incidence (for example, gender, age, but also residence). Dynamic, on the other hand, is information regarding the context of interaction with the brand for each individual user: people browse online, click, read, enter stores, buy and judge products publicly. To manage this complexity, technologies are needed that can not only manage different data formats, but also analyze and aggregate them in real time. The information to create segments is typically divided into three types:
