Businesspeople can now utilize data more selectively to gather relevant information and drive their work by decreasing time-to-market, improving product quality and meeting customer expectations. IT, accounting and sales management personnel need to adopt a "data for all" attitude as these roles have traditionally used and controlled data; gatekeepers or bottlenecks shouldn't exist anymore as your teams need access to tools that help them sort through all that clutter to make better decisions. Here are a few strategies and trends for mid-market managers looking to ensure data is everywhere.
Marketing managers assist companies in building brands, creating demand, increasing sales, and maintaining customer loyalty in an increasingly complex marketing landscape. Effective strategies today must balance team abilities with stakeholder expectations, customer satisfaction requirements and ethical or environmental considerations in their execution.
Scientific decision-making in today's complex environment requires scientific approaches for company operations and audience engagement to remain effective and comprehensive. Martech solutions offer data that will assist your efforts at creating positive customer reactions and interactions. Marketing managers must first be able to assess the needs of their target audiences. By collecting relevant data, marketing managers will be better suited for future decisions such as pricing strategy, marketing policies and KPI development.
Researchers from IDC recently conducted a study demonstrating that mid-sized enterprises prioritizing digital transformation are twice as likely to experience double-digit revenue growth and four times less likely to incur losses than those who do not invest. Data analytics technologies like artificial intelligence, machine learning, and predictive analytics are helping these mid-sized businesses compete on an unprecedented level. Size no longer represents an advantage in competition. While large corporations still possess superior resources and talent within their walls, mid-sized firms can now access similar intelligence, computing power and insights as larger corporations - often providing greater agility when responding to opportunities. Companies that demonstrate an impressive strategy in Big Data and analytics could emerge as tomorrow's market leaders.
Build A Frictionless Technology Stack.
IT managers face increasing complexity as businesses digitize more, with IT stacks growing ever larger and requiring greater management time to choose between various tools available for deployment. When multiple tools are utilized simultaneously, things may become chaotic and cumbersome. IT managers must ensure seamless and satisfactory data integration between internal and external clients, using reliable software tools to bring everything and everyone into one location.
IT managers must ensure the technology chosen aligns with how the rest of their company runs, with tech stack integration being an easy way to pinpoint which tools are essential or valuable to business operations. More connected systems mean more data available, improving business performance while creating greater scalability within an organization and allowing everyone involved in production and delivery processes to stay involved 24/7 - this ensures everyone can stay involved without interruption! With business SaaS providers taking care of database maintenance issues, IT managers can focus on ensuring everyone else can leverage integration effectively, ensuring it benefits all members.
Environmental Accounting
An increasingly challenging goal in supply chains today, balancing sustainable production, sustained growth, and environmental protection, can only become necessary through collaboration. Climate Change has become an increasing global priority, and stakeholders, from regulators to customers, have put increasing strain on leaders and companies to act. 76% of CEOs globally believe their success depends on moving toward a low-carbon, clean tech economy.
Finance teams are increasingly vital in revolutionizing how businesses and supply chains function while supporting sustainable decision-making. Financial data analytics aid finance teams by performing full cost accounting with greater accuracy and efficiency - improving accuracy and efficiency when reporting costs that were calculated or reported in previous periods; this reporting style also helps finance teams meet management demands of measuring water, waste and social footprint.
Month-End Reports Are No Longer Required
Finance and accounting teams have long relied on numbers to address problems. When these solutions don't suffice, however, CFOs have begun providing advice and support to CEOs and helping COOs and CISOs meet their goals within budget while adhering to business strategy - this makes their entire organization data-driven when sharing financial reports from CFOs with other executives. Accounting tools enable accountants to augment static reports with visuals. Furthermore, slice and dice functionality provides on-the-fly analysis capabilities for instantaneous responses to issues or opportunities.
Future financial statements provide each department in your company with an up-to-date profit and loss summary, so they can see where all customer's profits after taxes have been taken out. Everyone must have access to up-to-date revenue information and understand what it costs to service customers; returning orders are tracked separately with these orders so there can be accountability over return orders, size orders or repeat purchases. Active analysis has become the new paradigm in account preparation.
The Advantages And Difficulties Of Data Analytics Are Quite Related
As of now, IoT adoption has been driving Big Data analytics solutions. Sensors and devices are turning legacy machines into intelligent ones, giving manufacturing firms invaluable insight into production that they can then analyze using ERP systems, financial statements or customer satisfaction metrics. Sensors installed in brick-and-mortar stores that track foot traffic help enhance customer experiences across digital and physical realms. In contrast, IoT sensors used by farmers can monitor equipment, the environment, or crops remotely using drones.
Use cases such as these provide midsized companies across industries with massive opportunities. To take full advantage of them, AI-enabled analytical tools and IT infrastructure is needed; according to an article in Digitalist from 2019, mid-sized organizations often struggle to extract value from Big Data strategies due to two primary issues: internal culture (especially change management issues) and scalability issues that cause delays. With 5G and WiFi 6, IoT will become more reliable and faster, creating additional Big Data challenges in future. Failure to prepare could create further hurdles.
Data Types Used In A Marketing Mix
Effective marketing plans can have an immense impact on all four marketing mix components - product, pricing, placement and promotion - using data as guidance in these strategies to produce visible services or products which are competitively priced while being promoted through specific distribution channels. This process yields results that make these services and products widely visible while remaining cost-effective to produce.
Identifying which data should take precedence can be challenging, even though analytics offer plenty of insights that influence marketing decisions. Here are several areas in which data analysis and collection are essential in driving the business forward.
Sales Data
Data containing measurable metrics that reveal how and why services or products are sold include sales growth, annual revenue growth, churn rate, and net revenue retention rate.
These data allow marketing managers to make meaningful improvements in sales processes and pipelines, such as improving sales forecasting, identifying bottlenecks and creating better relationships between existing consumers and prospective new ones. Create an inclusive dashboard showcasing your revenue data with our 34 best revenue charts.
Customer Data
Marketers need to understand their buyers' identities to effectively target these groups with products and services tailored to meet customer expectations through content marketing strategies.
Customer data platforms (CDPs) and customer relationship management softwares (CRMs) are available to unify data from various sources into one comprehensive view of customers and manage relationships effectively. Marketing professionals use Insider, and Salesforce CRM systems strategically to leverage customer information in pursuit of business growth.
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Cisin Allows You To Combine Data From CRMs And CDPs With Other Data Sources In A Unified Warehouse
Understanding customer data helps increase success when selling to target markets. Customers' needs and preferences can generally be broken into four groups, depending on where you store the information about them:
- Demographic Data: Demographic information includes contact info, age, occupation and income data of customers who purchase products and services.
- Behavioral Data: Includes browsing patterns on websites/device usage/and preferred buying times of customers when using products & services
- Interactive Data: Which distribution channels and advertising tactics do customers typically favor?
- Attitudinal Data: Preference data, most often collected through focus groups, includes information about customers' preferred brands and services/products, opinions on them, and perceived values for any given business.
Competitive Analysis
You can enhance your business strategy and value proposition by studying your competitors' strengths and weaknesses. Big Commerce notes that analyzing competitors is an invaluable way to quickly identify major market players, understand their strategies, and determine resources an organization may use to dominate that space. These 11 tips will assist in measuring market competition and defining your value proposition.
Competitor analysis gives companies a measure of growth, as it helps identify which marketing strategies must be deployed to generate positive customer responses. For instance, customers might prefer watching humorous ads or video content over blog posts. This Comparative Analysis Template will enable you to identify your strengths and weaknesses.
Market Research
Market research should not be confused with competitor analysis; it describes and assesses a company's place and viability within its chosen marketplaces and business landscape. Furthermore, its main aim is to gain insight into marketing environments for specific products or services.
Market research serves several administrative, economic and societal goals, including refining marketing decisions such as public relations strategies and product design/development decisions. Some popular techniques used for market research are surveys, focus groups, interviews and customer observation - four common market research techniques used for such purposes.
Product Data
Remember that product data does not directly correspond with sales information; product data can help businesses increase brand loyalty and customer lifetime value by driving sales and acquisition strategies. KPIs, metrics and measures vary between companies. Product analytics should monitor customer engagement data to optimize customer journey experience.
The adoption rate of products, features, and updates is one of the key metrics used to judge the performance of these elements. Our guide to product adoption will teach you how to accurately gauge your business's growth and adoption rates, along with calculating product adoption rates.
5 Data Ingredients That Influence Marketing Decisions
Leveraging data to increase revenue may seem obvious; actionable insights increase leads and conversions as an organization with access to accurate consumer data can market its products or services more precisely and achieve superior results.
Organizations that pivot quickly can effectively utilize data strategies to create long-term marketing plans. Implementation of proprietary infrastructure and employing data-driven marketing can bring unfathomable successes.
Sales Data: A Key Ingredient For Marketing Decisions
Sales teams that leverage data effectively will only pursue leads with high potential. Analytics tools offer insight such as where leads come from, why representatives contacted them, and their preferred method of contact; all information that helps sales reps create buyer personas.
An American multichannel video programming service, found that 60% of customers who switched providers after moving homes became actively interested. They used this data to target new homeowners with tailored offers that outshone standard sales pitches. Furthermore, data quantifies which actions separate top sales reps and less productive ones: from leads prospecting, churn-reduction strategies and pricing, helping marketing managers evaluate which skills may need improvement within each team and creating KPIs (key performance indicators) to measure them against.
Product Data: A Key Ingredient For Marketing Decisions
Data regarding products encompasses their entire product life cycle and related processes and customer feedback. Many companies use customer-sourced data to inform marketing decisions; after an aggressive customer campaign to switch over from plastic straws, they switched to paper straws as part of an innovative program called Project Plastic Straw Free!
Brands can take pride in meeting consumer demand for greater sustainability through product data analysis, enabling more informed business decisions using its Change A Little campaign and marketing plan.
Customer Data: How To Make Marketing Decisions Based On Customer Data
Customers today are besieged with choices. To gain their attention and increase conversions, marketers need to craft personalized experiences tailored to customers' interests that help make them feel appreciated while increasing conversions. 75% of consumers now prefer retailers to use personal data collected about them to enhance the shopping experience. A business, for instance, could identify that one of its customers is an avid runner by entering into agreements with third-party data providers; then, its marketer could offer trail running-related items when that customer visits its website.
Product Recommender Engines provide valuable support. Data scientists combine all the personal marketing data compiled about clients to deliver content that resonates with prospects of varied backgrounds, niches and experiences. Search our list of recommended engines and identify which engine best meets the needs of your business.
Marketing ETL solutions are used by companies looking to personalize their marketing. Such ETL tools collect marketing data into one central data warehouse - Cisin, for example, integrates insights from 300+ sources, making creating recommendation pipelines much simpler. This platform helps users track contacts and leads across social media, email, and eCommerce platforms.
Market Research: Using Market Research To Make Marketing Decisions
Many brands use market research to inform their marketing campaigns. The Ready for Girls Campaign was introduced after careful analysis. It aims to disprove outdated stereotypes stating certain activities only belong to one gender, hence forming the basis of marketing decisions based on consumer needs.
Competitive Analysis: A Key Ingredient In Marketing Decisions
Analyzing competitors enables businesses to determine whether or not they are market leaders, followers or newcomers in their particular market. A marketing manager must use this knowledge effectively to remain competitive - typically by expanding marketing activities into areas with few competitors or targeting specific demographics.
An analysis of competitors would have demonstrated that South Africa, despite having its fast fashion outlets, possesses a growing middle class with purchasing power that craves European fashion.
Lower production costs and differentiated products are two primary drivers of competitive advantage for organizations. Many utilize differentiation by developing marketing plans designed to promote thought leaders, market challengers or flankers; by targeting untapped audiences, they displace competitors from peripheral markets.
How Can Mid-Sized Businesses Use Big Data Analytics?
Mid-sized businesses can leverage Big Data analytics for numerous advantages. Here are three use cases.
- Discover What Drives Customers: Data and intelligence innovations have revolutionized sales, marketing and customer service departments. According to IDC research, real-time information from smartphones, GPS devices, wearables and other internet-enabled devices combined with behavioral data from smartphones, GPS devices wearables or wearables combined with behavioral transaction data and business intelligence can enable brands to enhance the customer experience as well as innovate new products more quickly than ever. While marketing analytics platforms or automation platforms exist, more sophisticated experience management platforms take things a step further by merging operational data with customer insights combining operational data alongside customer insights gathered through operational data collection techniques allowing companies to innovate new ways of reaching consumers.
- Discover Trends and Opportunities: BI solutions used to be reserved solely for analysts, consultants and data scientists - but with today's self-service affordable BI platforms available as self-service offerings that anyone could use without needing expert data science knowledge for data visualization analysis purposes, clunky reports of old have become redundant and cost prohibitive for regular users without data science expertise to use real-time visualization for analyzing factors that impede performance or slow things down; brands can respond swiftly to emerging trends by quickly recognizing untapped markets with potential customer prospects while analytics platforms with AI/ML capabilities add immense value through guided decision-making capabilities for guided decision making decisions as well as predictive modeling capabilities that add great insight for planning purposes!
- Use Predictive Analytics: Predictive analytics solutions of today use more than historical insights for their prediction capabilities; instead, they draw data from multiple sources to predict outcomes and model impacts of various scenarios. AI-enabled platforms have proven themselves invaluable by brands for use cases including fraud detection, marketing campaign optimization and product development, among many others.
Mid-Sized Enterprise Data Analytics: Key Strategic Elements
Mid-sized enterprises don't have as much margin for error as major corporations like Netflix and Amazon; therefore, implementing a Big Data Analytics strategy may present both high risks and rewards to implement successfully. Here are some helpful suggestions for creating your customized Big Data plan:
- Define Your Goals: Determine what you wish to gain by setting out on this journey: for instance, are you seeking 360deg customer views, taking advantage of trends like deep learning, machine-learning and dark data or maybe predictive maintenance or streamlining operations to save both money and time - or perhaps using predictive maintenance or streamlining operations can save both. It is also essential that once collected, data has an impactful plan in place to use it later when available.
- At This Point: Outline Must-Have Features. Once you understand how analytics fit into the fabric of your business and its specific use cases, formulate your list of must-have features. Analytics-as-a-service platforms may offer additional flexibility by managing architecture for you while you simply pay per access point to insights.
- Research Closely: Investigate similar companies to find out their Big Data strategies and processes; study which tools they're using and their results; sign up for demos or free trials of different tools until one seems right for your needs; be wary of being seduced by promises made by customer experience platforms or IoT sensors and devices claiming they can turn anything into data; keep the problem in mind when considering solutions.
- Consult Experts: Mid-sized businesses may lack the talent or resources required for Big Data projects. An expert consultant can assist in identifying important use cases, align initiatives to long-term goals, select tools to support key objectives and work alongside your IT department to fill gaps and maximize abilities.
- Governance is of Utmost Importance: Compliance with CCPA/GDPR requirements has become mandatory for companies today, and failure could incur heavy fines that damage the reputation or even put businesses out of business. Furthermore, some state laws could introduce further requirements. Noncompliance fees could easily reach thousands per record, and one slip-up could cause irreparable harm to your empire.
- Address Storage Concerns: Many small and midsize businesses simply lack enough room to house servers on-site and enough staff members with adequate knowledge to maintain them effectively.
- Data Acquisition/Integration/Processing: Decide on an approach for collecting, integrating and processing your data that suits you; review available datasets; outline how insights might be implemented into real-time or batch processing systems if applicable; consult experts if needed for guidance in this regard - working with an expert is highly advised in this arena.
Data Analytics Is Essential For Survival
Plenty of evidence indicates that Big Data analytics no longer solely belongs to Big Tech or corporate America. With tools becoming more affordable and accessible, this could level the playing field and contribute to Big Data becoming ever more essential due to factors like rising customer expectations and COVID supply chain challenges.
Data Science and Analytics are indispensable skills when creating high-quality digital products, so 3Pillar offers you support to excel in the digital sphere.
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Conclusion
Digital marketing is a dynamic practice constantly evolving to adapt to emerging technologies and consumer preferences. As such, its data must be effectively leveraged to drive business expansion.
Many researches showed that organizations using data in marketing decisions had 23 times greater odds of customer acquisition, six times greater odds of retention, and 19 times increased profits than organizations not employing this approach. Furthermore, it allowed greater granular growth at individual levels and significantly greater ROI investment returns.
