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Daily Harvest x Burberry- finding the product gaps

The Burberry case describes the turnaround of a brand who had lost their identity, lost control of its key trait (quality), and alienated it's key persona in the process. Daily Harvest has a similar issue on their hands. Food quality control is at risk after customers got sick from dishes and Daily Harvest did not control the communication.

They need to think about a brand turnaround and messaging that emphasizes quality. They need to take steps to gain control over the supply chain, similar to how Burberry bought out some distributors and ended relationships with others.

Burberry also took this time to look at their product portfolio and make sure each product category is appealing to a specific gap in the market while not alienating their core customer. Revamping Daily Harvest's product line could send a signal to customers that they are turning a new leaf and realigning their products to their core identity/values.

For any business, and especially food, communication is key. Customers are willing to forgive you if you apologize earnestly and take the steps to show you're different. This would be a good first step for Daily Harvest.

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Black boxes

I spent much of my career before Sloan at SaaS companies who helped customers transform operations using data. Often times this was enhancing processes using AI (think data-driven dynamic decision making, rules engines, warning systems, etc.). One of the key tenants to all of the work was for AI to assist the human doing the job. This was partially because our society isn't legally ready to have an opinion on the role of AI in certain industries and also because the human provides nuance and a line of assessment that does not exist in models.

The "black box" of models used constantly came up as a discussion point. Certain customer counterparts wanted to know every detail of input and logic however documenting this information for each model was onerous to engineers and overkill for most business counterparts. It would be great if an AI resource existed that could review a model and auto generate a user-friendly description (maybe this already exists). As models get more and more complex and the infrastructure gets more technically complex how do we educate society productively so people feel empowered by and comfortable with the role of AI in their life? How do we give people the tools to understand where AI is supporting them and where AI is taking advantage of them?

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Concha y Toro

The decision on where to enter (or re-enter) a market to solidify a brand identity and enable brand expansion is an interesting study. There are many stories of brands that take a clear approach and successes are revered by experts.

For example, Tesla made the decision to start luxury and expand downward to more affordable models. Whoop decided to start with athletes and then expand downward to weekend warriors and now recreational athletes.

All three of these markets are selling durable goods (cars, wearables, wine) which require trade-offs on quality of raw materials, manufacturing, supply chain, etc. and price point to earn the best margins. However, from the article we see that consumer behavior in these markets is very different.

Additionally wine caries with it external market connotations which are more relevant than other industries (e.g. France and Italy carry a higher price point than Chile).

I do think it is important for a wine producer to enable economies of scale by producing many bottles under its ownership. Achieving this by producing multiple labels helps the brand target the full market (not just one segment) and capitalize on consumer's desire for novelty (especially in the premium segment). However, managing multiple brand identities takes capital and could eat into it's own profits under different labels.

I recommend Concha y Toro utilizes a top-down strategy as consumers are generally leveling up in their wine preference and palate. Therefore if they focus on attracting customers at the premium range, that connotation will follow to when those consumers need to by a lower-quality wine for a different occasion or when a novice wine drinker is purchasing based off reputation alone.

This is similar what top producers in Bordeaux do. They have a first label and a second label. The second label allows them to make wine from their slightly lower quality grapes yet still garner the reputation that their first label holds.

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Market Research

Great read about Market Research and opened my eyes to the complexity of trying to understand consumer preference. I understand where value can be gained from each approach but also see flaws in each approach too.

The first piece to highlight upfront is how important the 'fundamental law' in the Questionnaire section are to most marketing efforts. As a manager knowing "how will I use this data and how will I analyze it" is key to clearly define before budgeting out any project. There are some market research initiatives which are more exploratory by nature, however it is still crucial as a manager to define what you are generally aiming to understand with the research.

Regarding Experiments, I anticipate it's difficult for a manager to decide what needs to be experimented right now. A good experiment requires all else to be constant and they are costly; so defining the one variable and building a rigorous experiment around that is key. Additionally, avoiding any cross-contamination between two experiments should be top of mind.

From my nascent knowledge in market research, I find field test more reliable than lab test. I do not think people will be honest when they are intercepted and surveyed. Field testing seems much more accurate with the paired city or intra city approach.

I do understand the flaws with in depth interviews however I think they are one of the only market research methods that can get people to answer on a deeper level. The unstructured nature of them can be difficult to be confident in trends, however perhaps a team can think about adding a quantitative questionnaire at the end of an in depth interview when the respondent is more comfortable and more willing to be honest. In general, in depth interviews and market research may work best to identify "unknowns" and a first step to define what should be experimented or tested in the market.

In the case they speak about the perils of frame error and that it is costly to completely reduce it but they don't mention how to solve it. Are there companies that help with identifying a strong frame?

Overall this article was great background on market research methods. I anticipate many business areas: product, social media, packaging, distribution, sales, etc. all will be pulling on the marketing team to answer questions related to their line of business so it is important that the marketing team prioritizes and communicates clearly to get key business questions answered.