When one of the largest beverage brands was looking for an analytics solution that could help them monitor, manage, and increase sales globally.
Think Big Analytics, who had previously built a customised data lake for the brand, was commissioned to work on a consumer analytics program to boost sales. With bespoke data applications and tools, the brand was able to extract essential insights into consumer shopping patterns, media behaviour, and social trajectory — the result: more effective and targeted marketing and increased sales.
Do you believe that your brand can leverage analytics to drive sales? Sales and marketing teams depend on analytics to unveil commercially-relevant insights, thereby increasing revenue and profitability, while also improving brand perception. The right analytics can help a sales team to discover not only new markets and target audiences, but also areas for future development.
Gartner defines sales analytics as a tool “used in identifying, modelling, understanding, and predicting sales trends and outcomes. Aiding sales management in understanding where salespeople can improve. Specifically, sales analytic systems provide functionality that supports discovery, diagnostic, and predictive exercises that enable the manipulation of parameters, measures, dimensions or figures as part of an analytic or planning exercise.”
Some of the key areas where analytics can help sales teams are as follows:
- Customer Potential Estimation
- Sales Process Improvement
- Sales Force Management (including Size and Geo-distribution)
- Incentive Compensation
- Goal Setting
- Performance Management
- Sales Forecasting
- Predictive/Prescriptive Lead Scoring
- Customer Contact Analytics
- Sales Attribution (between Marketing and Sales)
LinkedIn’s sales data — which sometimes reaches close to a petabyte or more — is spread among its internal databases, Google Analytics, Salesforce.com, and other third-party tools. A single analyst on LinkedIn’s team ended up servicing daily sales requests from over 500 salespeople while creating a reporting queue of up to six months.
To centralise this disparate data, the LinkedIn business analytics team sought help from Tableau, using the Tableau Server to create a series of customer success dashboards. LinkedIn embedded the Tableau Server into their internal analytics portal, nicknamed “Merlin.”
Now, every week, 90 per cent of LinkedIn’s sales team visits the portal to track customer churn, risk indicators, and sales performance.
“We decided to focus on how to scale the solution that we built and really provide the scalability and empower our sales team to get what they need in time,” said Michael Li, Senior Director of Business Analytics. “Which is why we built this analytics portal. It became a one-stop-shop for salespeople to get what they need in a very self-service way.”
There are several benefits of adopting data science and analytics into your business so that you, too, can achieve that dream sales figure very soon. These include:
1. Customer Relationship
Whether you’re a B2B or B2C business, your customers expect a real-time response. Gone are the days when you could say “I’ll get back to you”. The information has become available at the tip of our fingers, and now products are too! Amazon, Facebook, Twitter and many other social media and high-performance ecommerce sites are fulfilling these expectations. This makes real-time analytics a must for any company aiming at increasing sales revenues.
A recent study shows that if online retailers retained 10 per cent more of their existing customers, they would double their revenue. Thus based on data-study, knowing who your customers are and building a good relationship with them can help retain customers and enhance sales.
As a startup, Airbnb has achieved a 43,000 per cent growth in just five years with the help of analytics. The reason for this is that they hired a data expert early on in their journey so that they could evolve at twice the industry rate. What worked for Airbnb? As a company, Airbnb characterises data using analytics for all decision making.
2. Price Optimisation
The retail industry is brutal in its competitive nature. Brands and products are at war to win customers over with better service, more offers and whatnot. The key, however, is to know how much a customer is willing to pay for your brand or product. Price optimisation is a big data analytics solution that helps you determine how shoppers will respond to different product pricing levels, which can maximise sales and profitability. Gaining real-time market visibility can help you monitor competitor pricing and thus enable you to put out deals or offers at the right time to gain maximum sales.
3. Customer Service
Yes, the customer is king, but your customers can often be your greatest critics. And if you’re not listening to what they have to say about your brand, then you might be precariously close to losing some valuable customers and thus sales opportunities. Real-time analytics can help you win-back a disgruntled customer and convert their loyalty for the long-term. Using real-time business analytics to map complaints, customer suggestions for new features and product line extensions helps in streamlining product roadmaps and reducing marketing costs.
4. Product Development
Are you selling what the consumer wants or are you spending too much time and effort to make your consumer want what you’re selling? Advertising and marketing campaigns worked well to create consumer needs some years ago. Today the scenario is a bit different. With more and more products available in the same category as yours, it takes more convincing to do the trick. Or you could be a smart business which develops their product to suit the consumer’s need.
Tom Davenport, the author of several best-selling management books on analytics and big data, notes how companies like Netflix and Amazon use analytics to understand the winning ingredients of popular TV shows, which they then use to inform their choice of future shows and maximise their chances of success.
5. Implementation and Action
Collecting and analysing data is just the start of the process of sales enhancement. To produce real results, it is important to use the information and insights that can execute and deliver change within your company. In other words, use the data to make your internal processes flawless. If analytics is only on the minds of the senior management, it is not only a waste of time and money but also risks your company’s reputation. Making sure that everyone is on-board the analytics train and ready to jump into action will ensure focused efforts towards achieving the set sales target.
Peter Baxter, managing director EMEA at Yellowfin, notes: “The inability to ask the right questions of data is often driven by a disconnection between data analysts and the business users or salespeople, which can prohibit sales leaders from asking the right questions from sales data at the right time. A lack of collaborative capabilities and the inability to combine sales data from one source with data from another are also common occurrences that prevent sales leaders from asking the right questions of their data.”
Data analytics is a key element on the path to becoming a customer-oriented business that also achieves a high sales figure. By drawing out meaningful patterns in customer and market behaviour, analytics can ensure you’re effectively targeting customers – both new and existing – as well as maximising your marketing impact.
The Top 10 Sales Analytics Solutions of 2019
- Sisense: An all-around business intelligence software that simplifies complex data preparation and visualisations, while allowing users to make better business decisions and intelligent strategies in less time.
- Looker: A business intelligence and data analytics solution that provides a 360-degree view of both sales and customer data. A premier web-based software, it analyses web-hosted and SQL information and can allow you to explore, analyse, and share data in real-time.
- Qualtrics Research Core: A survey software, this tool is equipped with data management, statistical analysis, segmentation, and targeting, as well as competitive benchmarking, allowing businesses to make better sense of your sales data.
- Zoho Analytics: A part of the Zoho productivity suite, it offers reporting tools that allow monitoring and analysing sales metrics, along with customisable data visualisation tools and dashboard layouts. It also has native Android and iOS apps to access sales information on-the-go.
- Yellowfin: A fully-integrated, end-to-end analytics software that processes big data from multiple sources, providing the user with data preparation, governance, and visualisation tools. The collaborative BI tools reinforce operations for agile sales teams, and its open API capabilities integrate with a wide variety of third-party applications.
- SAP BusinessObjects Lumira: An on-premise BI solution for large enterprises, it offers business data visualisation while connecting and analysing large amounts of information in one convenient platform. It integrates well with SAP productivity and BI tools, thereby eliminating the need for third-party applications.
- Tableau: Another BI solution built to help organisations to connect, visualise, and share data quickly. It offers a plethora of tools for data exploration and investigation, and with its collaboration features, it can be accessed from all desktop and mobile devices.
- SAS Business Intelligence: An analytics tool designed to discover, collect, and analyse enterprise-level data. It offers modules for visual analytics, statistics, and office analytics while allowing users to find metrics for predicting and forecasting trends, as well as optimising data monitoring.
- Microsoft Power BI: A suite of analytics tools, it scrutinises data and converts it into comprehensible reports. It also makes data consolidation easier as it allows importation from Marketo, Salesforce, Google Analytics, and more.
- IBM Cognos: An AI-infused BI platform that can be accessed via cloud or on-premise, it allows users to perform advanced analysis, analytical reporting, and other data exploration tasks. It can combine data sources, create dashboards, and has data-sharing functions where one can combine charts with an interactive report, which includes voiceovers and overlays.
By improving the service you provide, and by intelligently directing investment towards promoting brand advocacy, you can assure long-term growth. Sooner or later, you will come to realise that analytics matter.