1. What data are you capturing?
The first step in conducting an audit of your sales and marketing data is to identify all the data you're actually capturing. Quick hint - it's often far more than you think. Your sales and marketing data falls into three major buckets - customer, transaction and external data.
Firstly, there's customer data - this is all the information you maintain about your customers either on your CRM, in your loyalty software or even in spreadsheets maintained by your sales reps. This data can relate to their demographics (i.e. age, gender, location etc.), their behaviour (i.e. whether they visited a store or signed up on your website), and their needs (i.e. what products they've expressed an interest in).
Secondly, you'll have transaction data (which may or may not be linked to your customer data). This will include records of all the products and services you've sold to varying levels of granularity.
Thirdly, you may also be capturing external data from third parties that are related to your company. This could include the keywords customers are using on Google search for your category, the mentions of your brand on social media conversations, or the feedback on your product on e-commerce platforms.
By identifying all the data you're capturing, you get a clear picture of what you can work with as well as the major gaps you will need to fill in later.
2. What are your data sources?
The second step in the audit is to map the sources of your data. Today your customers will interact with you through multiple platforms such as a mobile app, website, email, social media, in person, or on the phone. Therefore, customer, transaction, and external data can flow from an increasing number of sources.
Mapping these different sources of data is critical to understanding its reliability (i.e. whether it contains outdated data), its cleanliness (i.e. whether it has the right spellings), as well as its velocity (i.e. the frequency at which it is coming in) and its volume (the size of your big data). By looking far and wide at the potential sources you can uncover rich untapped data assets.
3. What processes and systems are you using to capture and store data?
The third step in the audit is to identify what processes you are using to capture and store data. For example, in a retail environment, transaction data will be typically captured through a POS system via a barcode reader. However, a sales rep in the field might still write up details of a sale on a paper form which is later updated onto an ERP system. These two different methods of information capture have very different implications for data accuracy.
As well as identifying how data is captured, it is also important to identify how it is stored. For example, many of the legacy CRM and ERP solutions in use today only store data in relational databases. By contrast, the continuous stream of social media data you may be capturing is unstructured data which would be stored as NoSQL databases. The time taken to perform advanced analytics on relational data is often far greater than analysing data which is unstructured and stored as a NoSQL database. Therefore the type of analytics you can easily perform is dependent on how your data is currently stored.
4. How standardised and integrated is your data?
As the number of platforms through which you interact with your customers grows, so does the number of systems and applications for managing information. As a consequence, it is becoming increasingly important to standardise and integrate data across your organisation.
At a basic level, standardisation means checking that a correct and common nomenclature and categorisation of data is in place which will allow analytics to extract the right values. At a more advanced level, integration means understanding how information from different databases is brought together to form a complete view. For example, tools like ETL (extract, transform and load) can be used to combine information from different databases to enable analytics to be performed.
By understanding the current level of standardisation and integration of your data, you know how ready it is for performing advanced analytics.
5. How is your data currently used?
The fifth and final question to answer in an audit is how is data currently being used in your organisation. Today, most organisations are only doing descriptive analytics which gives you a picture of what happened in the past. For example, sales and marketing organisations will analyse past sales performance to decide the rewards for their sales force.
Meanwhile, more advanced organisations may be using predictive analytics to help model and forecast what might happen in the future. For example, building a model that integrates past sales data and other key variables that determine growth, you can create a more accurate picture of the future opportunity and set better sales targets.
Finally, the most cutting-edge organisations are using prescriptive analytics to decide the best course of action in a given situation. For example, the analytics engine can recommend how much you should change prices in a given market scenario to achieve your sales target.
By auditing the level of analytics being performed across the organisation you can benchmark your current capabilities and spot the potential to expand its application in the future.
By answering these 5 critical questions through an audit of your sales and marketing data, you can understand your company's readiness for advanced analytics and the key gaps you will need to address to become a truly data-driven sales & marketing organisation.
