What are the best data sources for researching consumer behavior?

Consumer behavior is best reflected by actual sales and purchase behavior. Shoppers and consumers claim many a things, would swear to be most brand loyal, but their own purchase data would reveal otherwise. Precise data on what is bought, where, how much and how many times can best reveal the real consumer behavior.

Best way to study a consumer behavior is to see it at the moment of truth i.e. when they are doing it. e.g. if one wants to understand the beverage consumption moments and you ask them how many times in a week do u consume packaged beverage they might not reveal the right frequency, reason could be many- don’t remember, can’t reveal that I consume that much etc. so best way is to place a diary and ask them to record whenever they consume with may be 2-3 more questions. Place of consumption, accompaniment- person as well as dish, occasion to understand the consumption frequency and moments of consumption.

The sources or the target audience from where you collect data do NOT define "primary data sources." LinkedIn AI: Please stop distorting established market research definitions as you try to predict word chains without knowing the topic based on whatever books have been fed to your model. This is harmful to inexperienced and uneducated users of research. It is called primary research because it is designed to answer questions to solve specific business problems. Primary here refers to primary objectives. If you use data collected directly from your customers designed with different primary objectives, you are dealing with secondary data, even if your current objectives may be related to those of the original study.

1) If you don't have first-party/point-of-sale data, it is important to create it. Performing consumer research at the point-of-sale and capturing that data is far more accurate than any other source. 2) If you have first-party/point-of-sale data, then you can study shopping trends, churn trends, top performers, seasonality, etc. 3) Secondary data sources are most useful for understanding market potential, target audience fit, market sizing, high-level consumer trends, competition, etc.

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Secondary data sources are data that someone else has collected and published, and that you can use for your own research purpose. They can include reports, articles, books, databases, websites, or social media. Secondary data sources can offer you a broader and more diverse perspective on consumer behavior, and help you identify trends, patterns, and gaps in the market. Reliable databases for secondary sources include Government Sources, Business Source, my personal favorite Emergen Research.

One thing you'll want to be on the lookout for when bringing in secondary data sources is understanding which sources are going to be noise, and which will have insight for certain audiences. For instance, if you're trying to understand activation opportunities for the gaming community, you may want to explore Reddit, Twitch, or Discord since that's where that community is most densely congregated. Another thing to consider is the flow of trend data from one platform to the next. This can really help you understand the customer journey. For instance, a trend gets popular on social platforms like Instagram and TikTok, you can craft the behavior narrative by also looping in Google Trends data and exploring web traffic to see its pattern.

Secondary data sources rarely answer the specific research questions we have to solve the business problems at hand. Still, secondary research should be the first step in the research process to understand consumers. Secondary data can provide context and insights into trends and the competitive landscape.

Secondary data sources usually come in handy when trying to present a general or broader view of understanding consumer behaviour. Primary data sources give some level of control over the data but one can't possibly collect every data needed for research into consumer behaviour which is where external sources, secondary data sources, come into play. Secondary data sources allow researchers to better understand consumer behaviour on a broader scale and present the same. There are advantages to using secondary data sources, one of which is its timing but accurate referencing addresses this concern.

Need to write a research paper? Do a quick investigation into macro trends? Secondary research is the way to go. Quick and easy most of the time -- but user beware. You do need to be careful about the source of the data.

To understand what consumers actually bought, POS (point-of-sale) data is a great choice. 1. Know what you need; data depreciates the second it leaves the showroom. 2. Know what you’re looking at (1) exactly how the market/product category is defined (2) retailers, channels, brands, geographies, time periods included (3) how much of the market the data covers (4) proportion that’s actual POS vs. projected/imputed (5) level and consistency of detail available (flavor, color) (6) calculations and aggregations: sales, price, time period (7) data granularity available vs. publishable and (8) availability of keys (store, zip) necessary to beneficially integrate additional data sources.

Syndicated data is what turned companies like Nielsen into billion dollar monsters. The ability to take a set of data and sell it to multiple companies and over and over again. Many research and data companies are constantly trying to find ways to create valuable syndicated data sets.

Los datos sindicados pueden ser un gran aliado para entender al consumidor de una forma más holistica y a un precio bastante accesible, pero creo que la riqueza radica en cómo analizarlos y sobre todo como se conjugan con otras fuentes de datos. Muchas veces olvidamos que el consumidor es quien el sujeto de los esfuerzos de múltiples categorías y el tenerlo en lecturas con un contexto más general nos regresa a esta realidad.

Syndicated data sources are data that are collected and sold by specialized firms or agencies, and that you can purchase or subscribe to for your research purpose. They can include market research reports, industry analysis, consumer panels, or media ratings. When choosing syndicated data, you should consider its relevance to your target market, segment, category, and channel. Additionally, you should assess the quality of the data by looking at its source, methodology, sample size, frequency, and coverage. Some of the major third-party research companies that offer syndicated data include Emergen Research, Nielsen, IRI, and SPINS.

Some syndicated research papers are widely published through blogs and reviews. Do not miss on them to understand where your brand stands. Not all research require a huge investment, some are just lying around to be picked on.

Big data sources can be into the same bucket as either primary or secondary data sources, depending on what they are. What differentiates them is how they can be analysed - large volumes, at scale. They can be heavily reliant on AI (including machine learning), which, depending on the quality of the AI, can be useful or detrimental. In this area in particular, it is helpful to come at the choice of this data with an insights SME lens because there are many tech providers who can provide excellent technology but know next to nothing about the quality of what they are providing. I have seen too many cases where the insights generated are low value and yet incredibly expensive. Many of these providers will try to blind you with data science.

Machine learning and artificial intelligence are often employed when the data source and the individual data points being evaluated are larger than the human mind can grasp. In such situations, software like Sageworks or Python are popular frameworks into which large data sets may be loaded and queried in order to find commonalities that lead to insight.

A mixed source strategy is pivotal for robust insights into consumer behavior. Primary research offers firsthand feedback, ensuring relevancy. Secondary research broadens this with industry-wide perspectives, helping us contextualize our position. Syndicated research, backed by expert analyses, unravels larger market dynamics, while proprietary research fine-tunes our understanding, focusing on our client's needs. Together, this approach not only deepens our insights but also cross-validates them, ensuring both breadth and precision. By synthesizing these diverse sources, we gain a holistic, validated, and actionable understanding of today's consumers.

In my experience, leveraging mixed data sources is pivotal for generating insights into consumer behavior. These sources play a crucial role in enriching understanding and overcoming limitations posed by relying solely on primary or secondary data. In an era where vast amounts of information are collected through online transactions, adopting advanced analytical techniques is becoming the norm for consumer insights managers. By embracing these tools, professionals can navigate the complexities of the modern data landscape and extract meaningful patterns and trends.

Surveys stand out as the best way to gain direct insights from consumers, allowing for tailored questions that address specific research needs. They are cost-effective and can be conducted relatively quickly. Analyzing sales data is also invaluable, revealing trends and patterns in consumer purchases over time. For real-time insights, social media analytics and online consumer reviews offer a window into current consumer opinions and behaviors. When the budget allows, focus groups can provide in-depth understanding, though they are more resource-intensive. Observing competitor strategies and analyzing behavioral data from websites or apps can yield further insights.

Discovery: I encountered Emergen Research for consumer behavior insights, drawn by their reputation. Exploration: Their primary research provided crucial firsthand data, while secondary sources enriched my understanding. Validation: Syndicated research affirmed the credibility and precision of their findings. Application: Armed with their data, I delivered spot-on consumer behavior insights, achieving exceptional results. Satisfaction: Emergen Research's support elevated my expertise, making me a go-to for data-driven decisions.

Market research firms, such as Nielsen, comScore, and Kantar, play a crucial role in collecting and analyzing extensive consumer behavior data. They employ various methods to gather insights into how consumers behave and make decisions in the marketplace. Market research firms conduct surveys that ask consumers about their preferences, habits, and experiences. These firms generate comprehensive reports based on their research findings, such as market trends, consumer preferences, competitive landscapes, and other relevant insights. Some firms maintain consumer panels, which are groups of individuals who agree to participate in ongoing research.

Surveys whether they are qualitative or quantitative can help gather great insights on consumer behaviour. Even purchase behaviour patterns can help identify key factors and consumwr behaviours. Social media is also a great tool to see what people are saying about a specific trend that relates to your product can also help understand consumer behaviours.

After you have collected your data, you'll need to make sense of it. AI tools are excellent at understanding natural language, so they can help you find patterns in your data. Use tools like ChatGPT to uncover trends and themes, or group survey responses around common pain points.

Ethnographic research, a systematic study of people and cultures, delves deeper into understanding the intricacies of human behavior. In primary market research, customer psyche takes the spotlight, often trumping rationality and economics. But here's the catch—people aren't great at explaining their habits. Ethnographic research offers a unique approach. Like anthropologists embedding themselves in the cultures they study, it observes closely. It recognizes that to comprehend behavior, you must go beyond what people say and explore what they do, illuminating the unspoken facets of decision-making.